MDM & RDM Quick Start Workshop

Aaron Zornes, Chief Research Officer, The MDM Institute

Here’s an excellent opportunity to improve your success as an enterprise/data/solutions architect or other IT professional embarking upon your first MDM or Data Governance initiative. During this fast-paced workshop, you’ll learn first-hand the best practice insights every IT professional must know to fast-track success and minimize risk. This is your pre-conference opportunity to meet with the “Godfather of MDM” to ask the questions and set your own personalized agenda to maximize your conference experience.

The speaker’s reputation for cutting through the hype to deliver a no-nonsense view of what you need to know will provide insights into proven approaches to delivering business value along with the insiders’ view of strategic implications of these fast-evolving technologies.

Combining presentations and case studies, this power session’s proven agenda is practical, personal and uniquely tailored on-site to the needs of the participants. The speakers will share real world insights from surveys and discussions with over 1,500 MDM programs to provide guidance concerning:

• Initiating a successful MDM, RDM and/or MDG program
• Convincing the business to take a leadership role with the goal to deliver measurable ROI
• Choosing the right MDM, RDM and/or MDG solutions despite a rapidly churning market — multi-domain MDM, reference data management, hierarchy management, identity resolution, big data, social MDM, semantic databases and more

Smart MDM - a Best Practice Guide to Design and Implementation

Mike Ferguson, Managing Director, Intelligent Business Strategies

This workshop focusses on the end-to-end implementation of master data management and tries to address the hardest problems that arise in an MDM project. It looks at the broader picture of information governance, data quality and metadata management before applying these to an MDM project. It also addresses how machine learning and artificial intelligence are helping to automate discovery, profiling, semantic tagging, and cataloguing of master data that is scattered across many different data sources and how it can be classified to know how to govern it. It then looks at the design of MDM systems looking at distributed maintenance of master data while still maintaining integrity, inbound integration of master data to consolidate it into an MDM system and outbound synchronisation of master data to supply both operational and analytical systems. Different implementations are considered including master data virtualisation when you have a hybrid state of some master data consolidates and some not. In particular it looks at what needs to be considered when dealing with data integration and data synchronisation to achieve best practice in design and implementation. The session covers the following:

• An introduction to data governance
• An operating model for governing master data across the enterprise
• Introducing a shared business vocabulary
• Metadata management
• Enterprise data quality and data integration
• Why Master Data Management? – building a convincing business case for MDM
• Smart MDM – Leveraging machine learning to automatically discover, profile, tag, catalog and classify master data
• The role of the information catalog in MDM and reference data management
• The main approaches to implementing MDM
• What kind of MDM system are you building? – a System of Record, Centralised Master Data Entry System or both?
• Understanding master data maintenance in your enterprise
• Best practices in designing master data consolidation
  • Data capture techniques
  • The benefits of standardising inbound data to an MDM system
  • Should history be kept in an MDM system?
  • Approaches to cleansing, and matching
  • Consolidation vs. virtualising master data to create an MDM system
  • MDM in the cloud – is this a better option?
  • Enriching master data using Big Data Analytics
  • Matching at scale – leveraging Hadoop and HBase for scalable master data matching
• Best practices in designing outbound master data synchronisation
  • Integrating an MDM system with an enterprise service bus for outbound synchronisation of operational systems
  • Schema and integrity synchronisation problems that can occur and what to do about them
  • Conflict resolution on outbound synchronisation
  • Design considerations when integrating MDM with ETL tools for synchronising data warehouses and data marts
• Distributed master data maintenance – can blockchain or NewSQL distributed relational databases help with master data integrity?
• Accelerating master data queries using graph query processing and graph analytics
• Maximising the use of data virtualisation in MDM
• The implications of switching to centralised master data entry
• The change management program imposed by centralised master data entry

Data Governance: A Critical Success Factor for Data Lakes

Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners

Data lakes have been characterized by a rush to technology innovation with little thought about anything else. While this approach leads to a fast technical deployment, it nearly always leads to wasted effort and resources as the needs of the data are ignored. This tutorial describes the leading role that Data Governance must play to make a data lake successful. The special needs of data lakes that Data Governance must provide solutions for are examined. Important among these are Data Acquisition, Data Legal Privacy and Compliance (both from contractual and data protection aspects), and the need for a Data Catalog. The way in which Data Governance must work together with a variety of other organizational units in the context of the data lake is also explored, with special emphasis on Data Architecture, Procurement, Legal, Compliance, and IT Security. Additionally, the utilization of a Data-centric Development Lifecycle methodology is described, highlighting how Data Scientists must be involved. The emerging tools for Data Governance and Data Management are also examined.

Attendees will learn:

• The basic structure of data lakes and the overall role of Data Governance
• The tasks that Data Governance has to perform for a data lake to be successful
• How Data Governance must work with other organizational units to achieve its goals
• A deep dive into Data Acquisition
• How a Data-centric Development Lifecycle approach is used for projects around the data lake

Bootstrap your Data Governance Program

Jan Henderyckx, Managing Partner, Inpuls

You’ve been assigned the task of implementing data governance in your organisation. What should you do in the first phase of your mission? Should I simply create a board of data stewards and hope for the best? Data Governance has now been around for quite a while now and we are starting to see patterns that explain the difference between success and failure. Understanding what the value proposition of data governance can be is a great starting point for scoping your program. Defining the vision and mission that is understood by the business will help you embed your data governance activities. The basic set of tasks that are required will strongly depend on the use case you are addressing. Supporting analytics is not comparable with setting up master data management or providing your management with reporting capabilities.

Attendees will learn:

• How you demonstrate data governance success and sell to your management
• What use cases can benefit from data governance
• How to define a good vision and mission for your program
• How you can put KPI’s in place
• What roles are required at the beginning of your journey
• What collaboration options are efficient for accelerating your progress

Making Enterprise Data Quality a Reality

Nigel Turner, Principal Information Management Consultant EMEA, Global Data Strategy

Many organisations are recognising that tackling data quality (DQ) problems requires more than a series of tactical, one off improvement projects. By their nature many DQ problems extend across and often beyond an organisation. So the only way to address them is through an enterprise wide programme of data governance and DQ improvement activities embracing people, process and technology. This requires very different skills and approaches from those needed on many traditional DQ projects.

If you attend this workshop you will leave more ready and able to make the case for and deliver enterprise wide data governance & DQ across your organisation. This highly interactive workshop will also give you the opportunity to tackle the problems of a fictional (but highly realistic) company who are experiencing end to end data quality & data governance challenges. This will enable you to practise some of the key techniques in a safe, fun environment before trying them out for real in your own organisations.

Run by Nigel Turner of Global Data Strategy, the workshop will draw on his extensive personal knowledge of initiating & implementing successful enterprise DQ and data governance in major organisations, including British Telecommunications and several other major companies. The approaches outlined in this session really do work.

The workshop will cover:

• What differentiates enterprise DQ from traditional project based DQ approaches
• How to take the first steps in enterprise DQ
• Applying a practical Data Governance Framework
• Making the case for investment in DQ and data governance
• How to deliver the benefits – people, process & technology
• Real life case studies – key do’s and don’ts
• Practice case study – getting enterprise DQ off the ground in a hotel chain
• Key lessons learned and maxims for success

Selecting from the Data Platforms to Create a Modern Data Architecture

William McKnight, President, McKnight Consulting Group

We must grow the data capabilities of our organization to fully deal with the many and varied forms of data. This cannot be accomplished without an intense focus on the many and growing technical bases that can be used to store, view and manage data. There are many now, more than ever, that have merit in organizations today.

Consider this non-mutually exclusive list:

• The Enterprise Data Warehouse
• Dependent Data Marts
• Independent Data Marts
• Analytical Data Marts
• Operational Databases
• Open Source Databases
• In-Memory Databases
• GPU Databases
• Columnar Databases
• Cloud Storage
• Multidimensional Databases
• Stream Processing
• Master Data Management
• (Hadoop) Data Lake
• Hadoop Analytic Workloads
• Training Data for Machine Learning & Artificial Intelligence (AI)
• NoSQL Databases
• NewSQL Databases
• Operational Data Store
• Graph Databases

This class sorts out the valuable data stores, how they work, what workloads they are good for and how to build the data foundation for a modern competitive enterprise.

You Will Learn:

• Knowledge of all major data platforms for your corporate data
• The role of Data Integration and Data Virtualization
• Steps in Moving to the Desired Platforms and Architecture

Managing Data Value Creation and Controlling Risk

Jan Henderyckx, Managing Partner, Inpuls

“Get rich in 5 minutes without transpiration”. You have probably seen many adds that try to convince you that value can be creating quickly without running any risks. Almost all of these claims are proven to be false, unless you recently acquired and resold Bitcoins.

What does this mean for data based value creation? It’s essential that data is properly classified to assure that your organisation interact with the data in the most effective and efficient way. Often data classification is managed by the information security team but they often have a restrictive view on information that is limited to security and protection. Keeping risk, privacy, security and value creation separately is not only inefficient but rarely leads to proper management of the data. The business is therefore overwhelmed with request to classify, define, assess, … Having a commonly agreed framework for classifying information and apply a concerted set of control mechanisms will not only improve your effectiveness but will significantly reduce the business workload. You will also be able to maximise the use of the data by capturing the usage constraints of the data as early as possible. Any type of data ingestion will be able to have the appropriate level of metadata that is required for applying the relevant data management tasks.

Attendees will learn:

• What the baseline is for governing data management
• How proper policy management provides a framework for risk control
• How to demonstrate regulatory compliance: GDPR, BCBS239, PCI/DSS, …
• How CIA classification levels can be extended to support Data Value management
• What lines of defence need to put in place
• Which roles and processes are required
• How to define requirements for data protection, data security, data integrity, data masking and data lifecycle management.
• How to assure data is used ethically

Data at the Traffic Lights! - Data Governance and Data Quality

Ian Wallis, Defence Infrastructure Organisation (DIO)
Godfrey Morgan, Defence Infrastructure Organisation (DIO)

Data is at the heart of every organisation but very few can certify that they have accurate, or good quality, data in all cases. As volumes of data grow exponentially the challenge increases, as does striking the balance between investing to maintain data to a high quality and the justifying the cost involved to do so. As data professionals, driving a coherent approach to data management is one of the biggest tasks we face and implementing data governance programmes can often be seen to be all cost and little benefit.

This workshop will explore the breadth of the task in establishing all the critical components that together lead to good data quality. At the same time, it will challenge those attending to articulate what good data quality looks like, and how to demonstrate value to the organisation from investing in data governance programmes. It will explore the lifecycle of data management, but will also endeavour to drive an interactive discussion to seek to provide real insights that can be deployed back in your own organisations.

Many data governance programmes are cited as being at a crossroads. Many have struggled to get traction, or been hindered by a lack of focus or commitment from senior stakeholders. Data quality is often reflected using a traffic light rating, hence the name of the workshop, and data quality is the visible evidence of the effectiveness of data governance.

‘Data at the traffic lights’ will enable attendees to:

• Understand the link between data governance and data quality
• Drive focus in data governance programmes to gain traction
• Explore how to realise value from data governance programmes through demonstrating benefits
• Learn from the shared experiences of the other delegates

Successful Reference Data Governance and Management

Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners

Reference data – often simply known as codes, lookups, or domains – is an area of enterprise data management that is becoming increasingly important. However, many enterprises have difficulty formulating governance programmes and management practices for reference data. This tutorial explains the overall structure needed for both reference data governance and reference data management. The very different roles need to manage external reference data (sourced from outside the enterprise) and internal reference data (produced wholly within the enterprise) are described. The options for environments for producing and distributing reference data are compared and contrasted. The significant role of semantics in reference data is also examined in detail, together with practical ways in which knowledge of reference data can be successfully managed. Additionally, the special aspects of quality in reference data are described.

Attendees will learn:

• What reference data is, how it differs from other classes of data in its governance and management needs
• The structures needed for successful reference data governance management
• How the semantic needs of reference data can be addressed
• How to deal with data quality in reference data content

Data Maturity: Evaluate It, Achieve It, Evolve It

William McKnight, President, McKnight Consulting Group

Maturity frameworks have varying levels of data management maturity. Each level corresponds to not only increased data maturity, but also increased organizational maturity and bottom-line ROI. There are recommended targets to achieve an effective information management program. The speaker’s maturity framework sequences the information management activities for your consideration. It is based on real client roadmaps. The class is a wealth of ideas for key quick wins to benefit the organization’s information management program.

While many organizations allocate budget to projects, the execution of the information projects (data warehouse, master data management, big data, analytics) provides innumerable decision points every day. It doesn’t take longer to make the best long-lasting decision. It takes know-how, which will be communicated in the class.

Students will self-assess their current information management capabilities in the class as we go through data strategy, organization, architecture, and technology, yielding an overall view of the current level of information management maturity.

This course provides a foundation for enhancing current capabilities and updating the strategy and plans for achievement of improved information management maturity, aligned with major initiatives.

You Will Learn:

• How to move your Data maturity forward while satisfying business need
• The importance of, and tips on, assigning workloads to their best platform, including introductions to Hadoop, NoSQL, Columnar Databases, MDM, In-Memory Databases, etc.
• What maturing data strategy, technology, architecture and organization look like
• The sequencing of activities in achieving information maturity
• Where your knowledge deficiencies may be in leading your organization, and therefore what to learn more of

Plenary Keynote: Excelling at Data in the Age of Digital Neo-Humanism

Roberto Maranca, CDO, Lloyds Banking Group

In a world where technological advancement is constantly beating any statement of impossibility, humans in their multiple roles of consumers, users and creators of data are now more than ever central to success in every CDO’s and Data Leaders endeavour. In fact human and data sciences are tantalising getting together to try to solve the numerous sociological and economical challenges of the 21st Century. This keynote will address the main factors to take into account, the methods to put in practice, and the trends to follow for the data practitioners.

What You Will Learn:

• Why Data scientist should become proficient in human sciences (as well)
• Why Big Data needs Big Emotional Intelligence
• How to win future challenges integrating humans and machines

Data Governance Keynote: Company Leadership in the 21st Century Comes from Data Leadership

William McKnight, President, McKnight Consulting Group

An increase in data leadership correlates to an increase in business success.

Every single item on a company mission statement relates to data at some level. It is from the position of data expertise that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data and projects that will deliver. After all, no matter what business you’re in, you’re in the business of information.

The data leader will anticipate the need — the voracious need — for data. If the need does not seem to exist, that is where to start. Commit to growing the data science at your organization. It’s simply not enough to be responsive to urgent requests and be the data leader that companies need.

The speaker will share from experience some of the hallmarks of mature, leading data environments that leaders will be guiding their data environments towards in the next few years, with the goal of helping true data leadership emerge.

• Top Initiatives are all about data
• Use of big data may define the winners
• Data professionals sit on the keys to business success
• How to bring initiatives to action

MDM Keynote: MDM-Driven Digital Transformation via “Systems of Engagement”

Aaron Zornes, Chief Research Officer, The MDM Institute

Market-leading enterprises are increasingly turbo-charging their digital transformation efforts by focusing on “master relationship management” style MDM. This next generation of MDM leverages Graph Database technology coupled with Big Data analytics. While traditional MDM purports to span the entire master data lifecycle, new dimensions such as Big Data, mobile, social, cloud and real-time are exerting tidal forces on the classic notion of MDM. Moreover, IT leadership struggles when selecting MDM software because the solutions are diverse with no single vendor able to meet all requirements and use cases. Given the prevalence of multiple MDM brands and architectures as a result, two relatively newcomers (Data Governance and Graph Database) are proposing to unify these silo’ed worlds to overcome both organisational and technical issues as well as market dogma.

The mega vendor-centric MDM offerings thwart the notion of heterogeneous data and process integration, and often lack pro-active Data Governance capabilities for end-to-end data lifecycle management. Concurrently, best-of-breed and niche vendors look to exploit this vacuum (cross-mega vendor governance and relationship management) yet are stymied by lack of resources and market traction. All MDM solution provider need to better focus on next-generation MDM requirements as we move from “system of record” to add “system of reference” and (ultimately) move into “system of engagement” wherein relationship-driven analytics form the foundation of MDM-innate, data-driven and context-driven applications to fully enable the digital enterprise.

Concurrently, mismatches in reference data (also called “enterprise dimensions”) affect the integrity of business intelligence reports and are also a common source of application integration failure. Due to the strategic nature of and difficulty to build/maintain custom reference data management (RDM) capabilities, savvy IT organisations and Finance departments are increasingly opting to buy and not build RDM solutions.

This plenary conference chairman keynote will review strategic planning assumptions such as:

• Determining what your organisation should focus on in 2018-19 to initiate “master relationship management” via Data Governance & Graph Database7
• Planning to leverage Big Data & RDM as part of an enterprise MDM program
• Understanding where MDM, RDM & Data Governance are headed in the next 3-5 years

CDO Keynote: Information Governance and the CDO x.0

Jan Henderyckx, Managing Partner, Inpuls

There are many styles of Information Governance that range from prescriptive to supporting. Picking the right approach that matches your ambition and positioning of data in your business strategy is therefore crucial. Is the evolution of the CDO, or the way of using data for that matter, a transformation that turns a caterpillar into a butterfly or is it rather an expanding circle? Most likely the latter. Information- and data governance is at the core of the data roadmap regardless of the end objective if you want to have a sustainable and compliant value creation. In this keynote Jan will put forward a model that provides the basis for establishing a data centric culture and that allows to integrate the different perspectives of data.

Attendees will learn:

• What kind of information governance styles can be applied
• Which organisational structure as most suited for creating data value
• How to best integrate with an analytics roadmap
• How data governance tooling can support the value delivery

Data Governance Without a Mandate

Guy Harvey, Enterprise Data Governance Manager, Jaguar Land Rover

Data Governance is as much about business change as it is about data. Changing the way data is managed, access or created requires people to see the value that can be gained by coordinating and consolidating efforts to manage data better. Sometimes, people just don’t have time to sit back and reflect on what could be or have the opportunity to learn about best practices, so a more dictatorial approach from an Executive Officer is needed to drive change. But what happens if that isn’t forthcoming and you are left trying to implement Data Governance without a Sponsor or a mandate? This presentation will take you through various approaches, options and tactics that Guy Harvey deployed at various companies to get things moving and make progress without a sponsor or mandate.

Best Practices of Data Governance Implementations

Werner Wiggers, Director, Effectual

What can you expect & learn from this presentation:

A. Concrete examples of successful Data Governance implementations will be presented

B. Data Governance deliverables (how to document owners, RACI model, role descriptions, change management aspects, Data Quality dashboards, issues lists and how to implement them will be shown)

C. Lessons learned (what went wrong/could be improved)

Summary: No theories but real practical stuff will be shown, by Werner Wiggers, who has a long track-record with Data Governance/Data Quality implementations, his expertise and passions is about DOING not TALKING about this topic.

Agenda

1. Background Speaker/Personal impressions

2. Why does Data Governance have growing interest ?

3. What drives CEO’s to adopt the Data Governance gospel ?

4. Examples of successful Data Governance implementations in NL:
– NUON/Vattenvall
– VOPAK
– Alliander
– Ministery of Justice/DJI
– STEDIN

5. Summary: DO’s and DON’ts

Discovering, Selecting, and Managing External Reference Data Sources

Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners

Reference data (also known as code tables and lookup tables) is becoming increasingly important in data governance and data management programs. A major component of Reference Data Management (RDM) is dealing with reference data that is governed outside of the enterprise, e.g. ISO-3166 Country Codes, and NACE industry codes. This presentation describes approaches to successfully dealing with these external sources. The difficulties of discovering and selecting the “right” external source are discussed, including how external sources can be mapped to conceptual models. The onboarding of external reference data, and the processes needed for this are also described. After the initial ingest, the need to keep up to date with the external source is explored, and the different update models that exist for these sources are described, with the various patterns that are available for RDM. Additionally, other concerns that will confront practitioners when working with external sources are covered.

Attendees will learn:

• Practical approaches to discovering and selecting external sources of reference data
• The processed needed to utilize external reference data and how to standardize these processes
• How to deal with changes to external reference data

Your MDM “Altitude” Depends on Your “Attitude”

Amramanjari Singh, Data Quality Analyst, Thames Valley Housing

Established in 1966, the Thames Valley Housing Association (TVHA) is one of over 1,100 Housing Associations in England. With a vision for everyone to have a chance to build their lives from a base of a good home, and a mission of providing good quality affordable homes and invest in communities, TVHA works together and towards making a positive difference to the society.

Inevitably, for an organisation which directly or indirectly impacts so many lives there is an absolute necessity to master data that relates to compliance requirements, such as repair work and fire risk assessments etc. for the Properties and the Residents. This requires hybrid, multi-domain mastery of reference, master and analytical data for accurate decision support, operational and regulatory compliance requirements. To support this goal, TVHA applying a commercial MDM solution that leverages smart algorithms and material design to simplify data stewardship, governance and integration.

In this session TVHA will be presenting how the extent to which an organization passionately embraces MDM (your “attitude”) directly impacts the benefits to the community they serve (your “altitude”). The speaker will address these topics and more:

• Establishing a flexible, scalable & robust housing association Property Model
• Enhancing “Properties” hierarchy model to leverage “Estates”
• Empowering staff for closed-loop involvement & informed decision-making

Lessons Learned from the IRM UK CDO Executive Forums Panel Discussion

Jan Henderyckx, Managing Partner, Inpuls

Five times over the last couple of years a selected group of CDO’s have met up for IRM UK’s CDO Executive Forum. The objective of the forum is to define best practices and exchange ideas on the role of the CDO in an organisation and to increase the impactfulness on the business outcome. As proper information usage is not just limited to the C-level the group decided that we wanted to share our findings and recommendations with a broader audience. Hence this session which is a compilation of “the best of” from our previous meetings. What delegates will learn from attending the session:

• How information can be used as a business enabler
• How to position your CDO in your organisation
• What capabilities are required to be successful

The next IRM UK CDO Executive Forum will take place on 16 May during this conference – if you would like to apply to attend please e-mail jeremy.hall@irmuk.co.uk

How Data Governance Enables Digitalization: Business Comes First – Then IT

Annika Runert, Data Governance Lead, Öresundskraft & Håkan Edvinsson, CTO, Informed Decisions Consulting AB

This is an inspirational success story how Öresundskraft, a Swedish utility and communications company, let Data Governance (DG) work pave the way for business improvements, GDPR conformity, and digital transformations. The unusual in this is that all this started as a business initiative, rather than, more commonly, a data quality IT issue, driven from pains and shortcomings. Öresundskraft is a comprehensive energy and communication company with 260 000 customers and producing 3500 GWh yearly, always from renewable sources.

This story includes:

• How the business went ahead of the IT department regarding data architecture skills.
• How managerial attention was established and how a convincing business case for DG activities was formed.
• How a “non-invasive” data governance approach was used to gain engagement among the business representatives.
• How a business-friendly data modeling technique enabled the business representatives to take the lead and the ownership of business information architecture.
• How the DG work is valuable for strategy fulfillment.
• Challenges, such as organizational changes, solution-focused IT-projects, maturity variations and short memories.
• The road ahead.

Rollout and Sustain Data Governance

Natalie Jakomis, Head of Data & Ben Evans, Data Governance Manager, Dwr Cymru Welsh Water

There needs to be a conscious effort to maintain ‘sustaining’ data governance. Rollout and sustain is not the last phase of a linear data governance process, but instead is a final step in a life-cycle. It is also never ending. Like data governance itself, the rollout and sustain phase of Welsh Waters Data Governance Programme represents the day-to-day activities.

Learn about the rollout and sustain activity Welsh Water are executing to ensure that everyone across the business understands how they are affected by Data Governance and therefore do things differently. Including:

• Adopting a data governance operating model and implementing the
  right delivery approach, so data governance becomes business as
  usual
• Collecting the right metrics, and reporting on success
• Socialising and embedding data governance as a behaviour
• Climbing the maturity curve
• Being sensitive to what is really happening versus what is desired to
  happen

Building a Master Data Organisation Across 9 Data Domains and 60+ Stakeholders – Rooted in Business Benefits

Gavin Mander, Head of Data Services, Morrisons Supermarkets
Ralf Teschner, Global Information Governance Lead, Capgemini

Morrisons is a Yorkshire food retailer serving customers across the UK in almost 500 stores and an on-line home delivery service. Uniquely, they source and process most of the fresh food they sell through their own manufacturing facilities. They serve over 11 million customers per week with over 110,000 colleagues.

Two years ago Morrisons launched an ambitious Master Data programme to improve a data management capability which was struggling to engage with business stakeholders. They started by prioritising Product, Supplier and Location Data Domains and have subsequently moved across a further six domains: Customer, People, Supply Chain, Manufacturing, Finance and Wholesale.

They have created a Data Management organisation with Management Board sponsorship which regularly engages with upwards of 60 business stakeholders. There is a small central Data Management team working closely with business stakeholders who have the freedom to make the right data decisions for their organisation.

The sustained level of engagement has largely been driven by a continued focus on delivering significant business benefit – they have listened hard and responded to what is important to their stakeholders. The Data Management improvements they’re making are directly contributing to Morrisons strategic goals of being more competitive, serving customers better and simplifying and speeding up the organisation.

Alongside this Morrisons have a sustainable and credible methodology; this started with a focus on teamwork by putting in place the right people with the right processes and, as they have matured, investment in technology such as Master Data Management and Data Quality tools.

Summary:

• How Morrisons secured and maintained active engagement across a large number of data domains and upwards of 60 business stakeholders
• How they worked with a large consultancy to put in place a self-sufficient and sustainable Data Management organisation
• Challenges they had measuring business value being delivered

MDM as a Global Business Service

Steve Heim, Data Domain Expert, AkzoNobel
Ard van der Staaij, Senior Manager, KPMG

Many organizations are in a journey to standardize and optimize their businesses in order to save costs and provide a better service to their customers. Master Data Management (MDM) should not be neglected in this journey. This session aims to convey the importance of MDM, to give practical guidance on how to service this as a global business service and which pre-requisites and pitfalls are relevant to take into account. AkzoNobel embarked this journey and is on its way to implement Master Data Services within their Global Business Services. For AkzoNobel this is a pre-requisite for standardization and integration of the global businesses.

Discover the benefits of organizing MDM as a global business service
How to setup the operating model of MDM within global business services and what can be delivered as a service
What are the challenges and lessons learned of the AkzoNobel journey.

The Resilience of the CDO

Sofia Alcala, Head of Data Governance, MBNA
Aaron Bradshaw, Data Quality Manager, MBNA

For years Data Management practitioners have struggled to get any attention from the board. Current Data Regulation provides the ideal environment to help to change this. How can Data Management practitioners take advantage of this and move from “unauthorized Data Architects” to Influencers in our organizations? What are the characteristics of an influential CDO? What is it that we need to do to gain a stable chair at the Board? What is the emotional price we are paying for it? Are there practical ways to embed our value into the organization from day 1?

• The challenge of changing the DNA of an organization
• A new Impostor at the Board
• The tangible value of Data Management
• Data Trust Index: a practical methodology to embed Data Management as BAU

Perspective Session - Start Your Journey to a Modern and Agile MDM Program with a Master Data Hub

Simon Dickerson, Technical Pre-Sales Manager (EMEA), Dell Boomi

Providing trusted data for business decision making is critical to driving competitiveness and success. As business stakeholders continually add more data sources to your hybrid IT landscape, traditional data management processes and integration facilities are proving to have outlived their original design. Some challenges that most MDM projects will face include:

– High Total Cost of Operation because your MDM projects are not one and done projects rather ongoing programs
– Slow implementations due to technology challenges that take their own time to show business stakeholders any business value
– Operational inefficiency that results from half-hearted MDM implementations that add to existing silos and don’t provide a true unified view of the single truth within an organization

An integration focused approach breaks with the old master data management practices with a hub-based mastering solution that meets the requirements of a data-driven digital enterprise. Join this session to learn more about:

– The value of a true cloud native master data hub solution
– How to get started with your MDM implementation in the matter of days and weeks instead of months and years
– Leverage true multi-tenancy advantages of a cloud-native solution by building data model using intelligent field suggestions
– Build trust in your master data across the organization by providing real-time data quality as a service
– Leverage built in capabilities to bolster your GDPR efforts to track data lineage, enforce data governance, and data deletion.

Perspective Session - Pragmatic GDPR - Single View of Person

Michael Hiskey, Columnist, Author and CMO, Semarchy

Cliff Gibson, Director, DBR Data and Product Owner, GDPR Mentor

DPOs, Controllers and Processors all have a hand in shaping the data subject information your organizations holds. Have you empowered all them to ‘search anywhere’ and ‘find everything’ for access, portability, rectification and yes (gasp) erasure with zero hand-holding from IT?

We didn’t think so. Rather than “teaching your mother to suck eggs,” this perspectives session is an ‘advanced class’ that will focus on practical experience from GDPR Mentor and Senior Enterprise Architect Cliff Gibson, and InfoWorld Columnist and Author Michael Hiskey.

There is no silver bullet. However, UK and other EEA organizations are putting in practice fast-path GDPR data solutions that solve for data subject access rights and requests without long consulting engagements that yield results in weeks. Lasting change is possible, and affords a myriad of unintended benefits from increased intimacy with the people data in your organisation.

Attendees will learn:

• How to get staff to care about personal data, using a carrot AND a stick approach
• Best practices from UK organizations that are out in front of this month’s deadline
• How to get executives, and peer department heads on board for smooth compliance

Perspective Session - Data Governance: From Theory to Practice

Pierre Delville, specialised in data governance and quality, will present and share how to deliver value with data governance using a step-by-step approach that has been tried and tested in an European retail bank. The presentation will provide insight into the design of a Data Transformation Programme and the creation of a Data Department from the ground including developing new tools and processes and covering regulatory and non-regulatory use cases.

Perspective Session - Modern Asset Catalogs - The stepping stone to AI

Jay Limburn, IBM Distinguished Engineer & Director of Product Management, IBM

Smarter businesses apply AI to learn and continuously evolve the way they work and fend off smaller disruptors. To extract full value from AI, companies need a data strategy that gives them access to all their data – no matter where it lives – in an environment that easily scales, provides self service and applies modern data governance and cataloging to empower data scientists turbo charge your journey to AI . Learn how IBM Watson Studio and IBM Watson Knowledge Catalog provide all the tools companies need to embed AI, machine learning and deep learning in their business, while enabling professionals to gain the most from their data to drive smarter business and lead industry-changing transformations.

Data Quality – What is Missing in the Success Equation?

Saima Iqbal, Enterprise Data Architect, Proximus

In this digital world, data has begun to be treated as an asset. Organisations that care about their customers and their financial success are running data transformation or similar programs to become data driven and to achieve the expected information quality level.  When data quality expectations are not met, what is missing in the equation then? This talk aims to provide answer to this question via:

• Define meaning of data quality
• Data or process problem
• Where are data pains
• Use it as a driver for data governance
• Plan to ease current data pain
• Plan proactive control
• Create link in between data quality and company
• Measure and share success

From Accessory to Necessity - Embedding Data Governance in Business Operations

HoChun Ho, Global Head, Data Governance and Management, JLL
Justyna Malarska, Data Management Lead EMEA, JLL

Effective data governance is a key enabler for business to gain competitive advantage. However, many of the components of a data governance program are not well understood or considered core business capabilities. Data stewardship, data policies and standards, data quality, critical data elements and thorough understanding of data assets are not always adequately funded. This presentation will review JLL’s journey to successfully transform data governance from a novel concept to an embedded capability in the business operations, supported by people, process and technology.

JLL launched the data governance function about five years ago. Like other organizations that established data governance, JLL faced various challenges as it moved up the maturity curve. With a clear vision, carefully planned timing, and practical execution, they were able to introduce the data governance building blocks and make them highly relevant to the business operations. In this presentation, JLL will share their unique approach and results:

• What are the data governance building blocks and how they contribute to tangible business outcome
• How to implement data governance and make it highly relevant to the business in every step
• How to proactively transform the organization with data governance

Global MDM – Strategy, Selection, Implementation, Service & Future Innovations

Joanna Walker, Global MDM Architect, AstraZeneca

AstraZeneca is an Anglo–Swedish multinational pharmaceutical and biopharmaceutical company headquartered in Cambridge. In 2017, it was the 11th largest drug company in the world based on sales and ranked 7th based on R&D investment.

This presentation will provide highlights of the best practices employed in the AstraZeneca Global Customer Master deployment that supports teams encompassing 65 markets worldwide. Items that will be covered include:

• Managing the selection process criteria to move to the cloud including various business & technical needs
• Identifying the cost efficiencies & agility resulting from replacing prior on-premise legacy MDM deployments
• Increasing the global adoption & contribution from thousands of sales reps through Reltio Cloud mobile UI
• Benefits of a built-in Data Change Request (DCR) process and workflow
• Control and enforcement to be able to standardize on a global model, while offering local flexibility
• Future expansion plans including GDPR strategies, and new data providers

Building an All-in-One Governance Hub of Geo-Referential, Business Partner, and Vessels Master Data

Matthieu Augier MDM IT Project manager, CMA CGM

Isabelle Azzarello, IT Manager MDM & Transversal applications, CMA CGM

The CMA CGM Group is present in more than 160 countries through its network of over 755 agencies, with more than 30,000 employees worldwide. With a young and diversified fleet of 504 vessels, the CMA CGM Group serves over 420 of the world’s 521 commercial ports. Through more than 200 shipping lines, the company operates on every one of the world’s seas. Its global presence and efficient ships like the CMA CGM BOUGAINVILLE enabled the CMA CGM Group to transport a volume of 18.95 million TEUs last year.

Pulling together a cross-functional IT & business team together, CMA CGM needed a single multi-domain platform that could govern data for customers/suppliers (business partners), vessels, and geo referential with a strong master data model and end-to-end workflow management. A top-to-bottom SAP environment, with strong adhesions to legacy systems, they had to look for a solution that would leverage the value of that investment; at the same time, a conventional master data governance solution was inadequate for their needs around agility, fast time to value, and complex workflows.

CMA CGM built an operational system for thousands of users all over the world with the Semarchy xDM Data Hub. Linking legacy internal and SAP systems, it is a single, cost-efficient platform for data stewards to provide shared services across shipping activities, and user interfaces. The 24/7 “always on” system is a critical tool in the complex connected systems landscape, regulating data that need to be validated with tight SLAs.

Attendees will learn best practices in:
• Selecting, implementing & integrating agile Data Hubs that include MDM, Governance & Application Data Management capabilities
• Overcoming challenges from home-grown & legacy systems that need to be maintained alongside & integrated with new platforms, including SAP landscape
• Delivering faster ROI & higher customer satisfaction via cross-functional teams that can connect IT & Business processes

Determining the Value of our Data

Dr. Johanna Hutchinson, Head of Data, The Pensions Regulator

Whilst our business partners pivot between the highs and lows of the hype curve on their data journey, the data team are tasked with steering the business towards where the data can have the most impact. The value of data differs by business and indeed by business area as does the impact that it can have. But where is the greatest value to the data we hold? Is it always in the profit margins; efficiency and increasing sales? What’s the true value of data which runs public services, identifies criminals, gives greater insight on a sector and manages our personal records? How can we find this for our organisation and how do we lead the organisation to resource and invest across a profile of high impact data-driven initiatives.

• Innovating – In search of data to add value
• Learning where true value lies in the business
• Landing this work back into the business

The Data Governance Salesman

Michael McMorrow, Principal, MMM Data Perspectives

Success or failure of Data Governance programs is mainly down to the level of genuine commitment across the various human actors involved. Data Governance leaders should learn the psychological techniques deployed by great salesmen who know what subconscious buttons to push to sway behaviours.

This presentation will explore, with fascinating illustrations from psychological research and the presenters experience, some of the consistent flaws in human behaviour which drive decisioning and which skilled influencers can exploit.

Topics covered will include:

• Reciprocation – uncomfortably strong desire to pay back favours
• Commitment – fixation to avoid revisiting previously made decisions
• Social Proof – urge to mirror the beliefs and actions of others
• Authority – disturbing degree of submission to direction from authority figures
• Subjective Biases – shortcuts to decisioning based on pre-conceptions.

We need a basic understanding of the messy way that people think, in particular if we want to influence them to do something that they don’t particularly want to. A great salesman, or a great Data Governance leader, makes them think that they really, really do want to.

Top Tips for Doing Governance

Ieva Langenfelde, Global Master Data Governance and Quality Manager, FrieslandCampina

In this session, Ieva will share lessons learnt at FrieslandCampina while they were setting up Data Governance from scratch.

• Tip one: get ready to get dirty. Be ready to work hard, learn a lot, and be armed with lots of patience. Hear what were the (hard) lessons learnt for FrieslandCampina, and how to best prepare for the ride.
• Tip two: demystify the scary monster. Make it not scary. Speak the human language, give real examples. Be one of them, stump speech won’t work.   Ieva will share how they turned the scary monster into their pet.
• Tip three: get the right kind of crazies in your team. You have to have the right people to do this job. It takes two to tango, but it takes a whole bunch of crazies to do governance.

Dynamic and efficient product data quality management with characteristics and machine learning

Björn Bayard , Bayard Consulting Group

Digitalization is placing ever-increasing demands on product information in the retail sector. Very often purchasing, category managers and even content teams no longer know which of the many possible information on each individual product should really be maintained. We show how product class dependent characteristics and machine learning can be used to efficiently ensure product data quality.

Transforming Public Sector Services via MDM

Mark Brennan, Analyst Project Manager, London Borough of Camden

In 2013, the London Borough of Camden developed a Residents Index using IBM’s MDM platform. Camden realised that if they were to develop optimal joined up services for their residents then having an accurate citizen record was essential to this. The Camden Residents Index (CRI) unites information from multiple council data sources to create a single, consistent view of residents across the borough and the council services that they are accessing. The system uses sophisticated probabilistic matching techniques to link records from different business systems together to produce a single golden view of the citizen and the household.

During this session you will hear how one of London’s largest boroughs has put an MDM solution at the heart of its council-wide transformation. Mark Brennan was the main technical lead at Camden during the implementation phase of the project and has been heavily involved with the system since then. He will discuss the drivers behind the project and will give an overview of the system. He will run through some of the implementation challenges involved in linking data sets together and the key lessons learnt from the project. He will also run through how the system is currently used in Camden, the benefits realised since its implementation and Camden’s plans for the future. In addition, he will discuss how technology alone isn’t the solution and how an MDM system must fit into wider a data strategy/data governance programme.

Topics to be discussed include:

• Embedding MDM right into an enterprise’s Digital Strategy to support Single View capabilities across former silos of information
• Developing MDM as a key foundation enabler to support council wide Business Intelligence & advanced analytics
• Planning for the next MDM phase by placing MDM at the heart of the council’s data strategy

Data Strategy - Getting Value from Data for the Public Sector

Kevin Fletcher, CDO, HM Revenue & Customs

HMRC sits at the centre of government, raising revenue of £575bn to fund public services from over 5 million business and 45 million individual customers. Being at the centre of government, HMRC are perfectly placed to use the value of their data to deliver sound policy advice, improve services, support customers pay the right tax and target interventions on those that choose not to pay.  All, of this is brought together in the HMRC data strategy.

In this talk, Kevin will explore how HMRC are getting the fundamental building blocks in place to establish a truly data-driven organisation, recognising the privilege and responsibility they have with the data they hold.   Kevin will discuss how HMRC are bringing together sophisticated tools and analytical techniques to gain insight and value from the data to drive business change. But, none of this is sufficient without consistent focus on culture change within the organisation, which this session will also explore.

In this session you will learn:

• About HMRC strategic transformation and the central role data plays in this.
• How to build a data strategy in a large operational organisation, recognising the importance of ministerial priorities and the complexity of the activities in the organisation.
• The key ingredients for embedding a data culture at scale.

Multi-Platform Data Management - The Critical Importance Of An Information Catalog

Mike Ferguson, Managing Director, Intelligent Business Strategies

This session will discuss:

• The data deluge – new data from hundreds or thousands of data sources
• The complexity of managing data in multiple data stores on-premises and in the cloud
• Approaches to multi-platform data management
• Bringing order to chaos – the role of the information catalog and data management platform
• Information catalog capabilities and technologies
• Data ingestion and automated data discovery
• Governing data across multiple systems using data classification and tag based policy management
• Using the catalog to accelerating information production
• Beyond data – adding data and analytical artefacts to the catalog
• Shopping for data – Information consumers and the catalog

A Year in the Life of Data Governance – from Conception to Teething

Lindsay Towler, Product Information Manager, Arco
Stuart Squires, Managing Director EMEA, Comma Group

This talk explores Arco’s recent journey to set up their data governance organisation. They will focus on “why” Arco needed data governance, looking at the drivers that led to them embarking on their journey and how it fits into their wider strategic objectives. They will then delve into “how” they went about setting it up – the challenges they faced and the approach taken. They will then focus on what has ben delivered and how this has enabled Arco’s business to prepare for what comes next on their data journey. The talk will then reflect on learnings to date and explore what could have been done differently? Is the data governance supporting the initial “why” that led them to begin and crucially what comes next?

What delegates will learn:

• How to prioritise your focus when embarking on a data governance journey
• Getting the basics right sets you up for future success across new domains
• How to make sure you embed Governance into your organisation rather than see it as a one off project activity

Non-Intrusive Data Strategies for Customer Engagement

Mehmet Orun, Data Strategy Leader & Sr. Director, Product Management, Salesforce

End-users ask for Customer MDM solutions to have a holistic understanding of their customers, however with many implementations, business value of accessing this 360 degree view is delayed.  Many of the frequent questions asked by enterprise level managers of market-leading Cloud solution provider Salesforce include: Does SFDC have any MDM capability? How would it integrate with MDM hubs? How do we prevent duplicates?   Should we block users from creating Accounts? How do we set up security so people only see the customers they should?

Cloud-based data services, integrated into the application platforms, enable many enterprises to realize benefits of traditional MDM solutions faster, while providing a stronger foundation for enterprise-wide MDM solutions.  This session will discuss how to enable organizations to get to an improved degree of customer understanding, and how “controlled redundancy” and in-platform services can yield greater user experience and engagement in business applications.  The presentation will also provide a framework of iteratively reaching better managed customer data across faster project cycles.

Topics include:

Shifting from technology- to business-focused data strategy definition
Overcoming lack of governance rules & process controls which cause loss of insights
Demonstrating the business value of Customer 360 “mastery” – Quality, Integration *and* Visualization – on both data quality & business operations

Driving Customer Centricity at Elsevier

Catherine Taylor, Head of Customer Data, Elsevier
Tom Perry, Director of Software Engineering (Data, Insights & Integration), Elsevier

Elsevier is part of the RELX Group, a multinational information and analytics company listed in the FTSE 100. Elsevier provides information and analytics that help institutions and professionals progress science, advance healthcare and improve performance for the benefit of humanity. As an information company it is imperative that Elsevier has high standards for the management of its own business data and is able to function efficiently and leverage business insights. This session will cover a case study of the journey Elsevier is taking to put the customer at the centre of their business. In May 2017 after a 2 year project Elsevier went live with a centralized Customer Hub to master customer information and drive a single view of organizational customer touchpoints across the Elsevier business. Attend this informative case study session to learn about the challenges faced and overcome and the many lessons learnt so far on this journey. The Elsevier environment is specifically challenging due to the volume of systems accepting customer data entry and conflicting requirements from multiple different business units. Hear about the general appetite awoken at Elsevier for clean de-duped customer data and the overall vision for MDM at Elsevier beyond customer. Specific topics to be addressed will include:

• Pain points within our business that made us realise the need and justification for a customer master
• People, processes and technology that allows us to have a joined up approach to solving our problems
• Business benefits realized and unexpected insights gained

Data Strategy Forever, for Everyone.

Mark Woodward, CDO, The National Trust

The National Trust exists forever, for everyone. This presentation will talk about the challenges & aspirations in delivering & consuming data “forever, for everyone” .

• The challenges with bringing a traditional, values based organisation on a Digital Transformation
• Why all this “data stuff” isn’t as hard as we may think it is
• The relationship between IT and the Business and why it’s as critical as ever

Plenary Keynote: Data - The New Business Imperative

Anwar Mirza, Global Head of Data Governance, TNT

The need for CDOs, Data Scientists and Data teams is now more readily accepted, understood and mainstream in many organisations. Does this necessarily mean that the Data problems, solutions and value are equally understood and accepted? Are the different departments of an organisation adequately geared to deliver the benefits promised by the CDO?

This engaging Keynote will challenge the key players on their collaboration, evangelism, marketing, education and general awareness of the Data function. Anwar sets the scene for the conference to encourage attendees to structure their Data responsibilities in a consumable manner. With some practical experience of success and failure, he explains what must become the norm in order for the CDO and Data function to be accepted, grow and remain sustainable.

Data Governance Keynote - A Practical Guide To Setting Up A Working Governance Organisation

Gerard Bartley, Manager Global Master Data, Jacobs Douwe Egberts

This session will walk the audience through the main steps in setting up a master data governance organisation, using a tried and tested methodology.

The topics covered will include:
Planning out the programme, scoping it, costing it, etc
The governance framework
The data rules and dimensions (and who owns them)
The organisational structure and how to find owners
Communication tools and timing, to secure owner engagement

Delegates should be able to take away:
A clear vision of how data governance is set up
Practical guidance on building a master data governance organisation
Key risk areas and how to deal with them

MDM Keynote: Field Reports for 'Top 20' MDM Solutions

Aaron Zornes, Chief Research Officer, The MDM Institute

Evaluating MDM solutions is comparable to purchasing your first home— too many new variables, lack of transparency in the pricing, and high-pressure sales tactics.

On top of this pressure, IT executives must contend with the marketing dogma of ongoing “stack wars” among the mega vendors and the dogmatic “we are the world” viewpoints of MDM and (even) Business Process Management (BPM) vendors.

To cope during 2018-19, many large enterprises will increasingly mandate a unified approach to governance of master/reference/meta data albeit with the option of more than one MDM solution provider.

This “no holds barred” keynote session will focus on the why and how of both MDM platform technical evaluations by providing insight into:

• Understanding the pros & cons of the dominant architectural models & evaluation criteria— e.g., pro-active data governance, identity resolution, hierarchy management, scalability, Big Data & Cloud integration capabilities, etc.
• Assessing the vendor landscape— e.g., registry, data hub, ultra-hub, Cloud/on-premise/hybrid, data service provider, BPM-centric, IPaaS, etc.
• Applying a rigorous methodology to product evaluations for both mega vendor solutions (IBM MDM, Informatica MDM, Microsoft MDS, Oracle CDM, SAP MDG, SAS) & more pure play (Ataccama, Enterworks, IBI MD Center, Magnitude, Orchestra Networks, Profisee, Riversand, Semarchy, Stibo, Talend, Teradata, TIBCO, et al)

GDPR Keynote: Data Governance and Regulations: A Case Study on the Implementation of GDPR

Dhivya Venkatachalam, Director, Data Synergie

This session will focus on the relationship between Robust data governance and Regulations – Leveraging the data assets and the data organisations to address the legal and regulatory requirements. New regulations are being introduced all the time. Investing in a sustainable data ecosystem is essential to address these regulations throughly. Good data infrastructure gives us an understanding of what data we have, who owns it and who accesses it, how and where it is processed, what it is used for and how it is stored, archived and destroyed. This session focuses on building the foundational data organisation that can answer all these questions and help us manage our ever changing regulatory needs. This session uses General Data Protection Regulation (GDPR) as a case study to show how Data Governance can be effectively and efficiently used.

What You Will Learn:

Build the foundational data governance Infrastructure
Build the data organisational ecosystem to support the data infrastructure
Use the Data Governance organisation to manage regulatory needs.

Promoting a Data Centric Approach Within the Intellectual Property Office

Mike Fishwick, CTO, Intellectual Property Office
Mary Drabble, DG Consultant and Customer Success Manager, Agile Solutions

Agile Solutions were engaged “to perform an assessment of the IPO’s data governance maturity and to qualify a to-be data governance framework, based on people, process and technology levers”.  Their goal was to identify enablers and mechanisms through which the IPO can set up a sustainable data management framework and develop and mature its in-house capability.

In this session, hear directly from their client, about the challenges they faced including:

• Raising awareness of data management processes and best practice
• The obstacles: organisational, cultural and resource constraints that we had to overcome
•  Educating the IPO about the importance of data governance

Relationships Matter - Doing Governance with Graphs

Nick Jones, Manager, Data Governance, Multifonds

Two years ago, Multifonds presented details of how they managed to start small and cheap in Governance. At that time, they also outlined a number of the areas they were hoping to advance into. This is a ‘progress-report’ in which they will first outline how they have used and enhanced the original dictionary to support development of a real-time data mart, and secondly cover the steps they took that led to Multifonds to selecting and starting implementation with a graph database that will take them forward towards their intended Meta Data Hub.

Multifonds are software developers, and that graph based Hub will eventually cover (inter alia) the meaning of the data stored by their software, its location(s) in storage, its usage in code and reports, and the relationships between all of these. It will also cover both the design and the implementation aspects of the PDLC; improving oversight.

This session will show:

• Starting small and cheap worked.  Multifonds will illustrate how they have continued to extract value from the original investment.
• No commercial offering had full-enough coverage in a low impact, low-cost solution to meet the wide range of needs Multifonds has from the Meta Data Hub
• The approach used in graph databases for relationship modelling fits particularly well with their current governance needs, and provides maximum scope for future extensions.

Underpinning an MDM Approach with a Data Quality Strategy

Ellie Fitzpatrick, Data Governance Manager & Bethany Lancaster, Senior Data Governance Analyst, Yorkshire Building Society Group

A period of acquisition and mergers with a number of other building societies introduced increased systems and data sources with differing data structures and quality levels, posing challenges across all aspects of master data management: standards, definitions, creation, maintenance, quality and governance.

It has long been recognised that MDM is as much about people and process as technology, with technology being the enabler. At YBSG, following the implementation of our MDM technology, challenges remained with the organisation’s approach to data and cultural change needed to drive improved MDM. The role of the Data Governance Team at YBSG has been to drive this business focussed approach to MDM, underpinned by a business focussed Data Quality Strategy.
This case study from the Yorkshire Building Society Group will cover:

• Using the DMAIC model to set out our approach
• Building the capabilities required
• The progress made and challenges faced

The Top 20 Implementation Partners (Global & Boutique)

Aaron Zornes, Chief Research Officer, The MDM Institute

Consultancies (usually) provide excellent value in helping enterprises develop strong master data foundations for their digital transformation strategies.

Given the substantial investment that enterprises undertake with consultancies as implementation partners, the selection of the appropriate partner(s) must be given considerable scrutiny – not only to contain costs, but to insure success of these vital MDM, RDM and Data Governance initiatives. Implementation partners (a.k.a. external or managed service providers) such as systems integrators and specialist consultancies are more important than ever – not just because of the services:software ratio for such projects (universally ascribed as approaching 4:1) but precisely because of an ongoing shortage of experienced MDM, RDM and Data Governance professionals.

In an MDM Institute survey of more than 1,700 such programs, systems integrators (SIs) have been seen as essential to the success of the majority of such projects, yet previously incumbent SIs are becoming less dominant. Expert assistance from SIs will remain especially critical and problematic to the success of these programs during 2017-18 as organizations deal with a shortage of MDM/RDM/MDG experience, and tool expertise.

This session will also provide up-to-date Field Reports on the top 20 global and regional specialists in the MDM and Data Governance market. To further assist organizations, it also includes findings from a year-long readiness assessment of more than 135 leading consultancies to provide a balanced view of:

Understanding why SIs are essential to the success of your MDM, RDM & Data Governance projects
Structuring how an enterprise should evaluate the capabilities of “new” potential SI partners
Orienteering the SI landscape for both the traditional leaders as well as the new “young Turks”
Global consultancies – Accenture, ATOS, Capgemini, CGI, Cognizant, Deloitte, et al
Regional/best-of-breed specialists – Adastra, Affecto, Arhis, BAE Systems/Detica, Business & Decision, Edifixio, Jibes, et al.

GDPR as a Data Governance Booster

Alberto Villari, Data Governance Manager, Yoox Net-a-Porter Group

Alberto will discuss how committing to meet Global Data Protection Regulation (in force from 28th May 2018) encouraged the Yoox Net-a-Porter Group to deeply reconsider and review their attitude towards Data-as-an-asset, and, in that, taking actions (people, programme, processes etc.) to put in place a sound Data Governance framework around Customers Data processes and lifecycle.

Perspective Session - Future-proofed Cloud MDM - Organise ALL your data for continuous self-learning.

Ramon Chen, Chief Product and Marketing Officer, Reltio

MDM is the foundation for reliable data that sets the tone for powering applications, analytics, and business initiatives across the enterprise. However, many companies have started to define a core data foundation which organises ALL their data, and extends beyond just MDM.

This action-packed session will forever change your view on MDM as it covers how you can:

• Get up and running with Cloud MDM on any domain in weeks
• Uncover relationships across people, products, places and organizations, through powerful built-in graph capabilities
• Have RDM as part of the platform, without having to license a separate tool
• Seamlessly incorporate transactions and interactions to deliver a 360 view
• Automatically get new data-driven applications that business users can access on mobile and desktop
• Utilise on-demand Google-like search across all your data, with point-and-click segmentation
• Naturally solve compliance issues such as GDPR just by focusing on organising your data to drive new business initiatives
• Take advantage of AI, Machine Learning and predictive analytics with pre-built algorithms and a Data Scientist ready environment
• Gain continuous awareness of the quality and business value of your data with scores and metrics in the form of recommendations that help focus your efforts
• Future-proof your MDM efforts, allowing you to take advantage of new capabilities and technologies with no impact upgrades, across multiple-clouds

Perspective Session - WODA – the first 100 days

Guy Bradshaw, UK GM, Entity Group and Neill Crump,  CDO of WODA.

The Worcestershire Office of Data Analytics (WODA) is an organisation jointly funded by public sector partners including Worcestershire County and District Councils, Police & Fire Services, NHS, Worcestershire Local Enterprise Partnership and the voluntary and community sector. This presentation will describe how WODA will drive ground-breaking enhancements to the lives of citizens across Worcestershire including:

• How strategic management of data is critical to the success of Worcestershire
• The objectives and outcomes of the data-sharing initiative:

•Empowering county strategic decision makers and front-line staff with information to enable informed decisions and successful interventions
• Using ‘data as an asset’ to transform services and in doing so empower residents, enhance economic growth and connect communities
• An overview of the interventions ranging from the safeguarding of children and vulnerable adults to the enhancement of vehicle flow through real-time traffic analysis

Join Entity Group’s UK General Manager Guy Bradshaw and CDO of WODA, Neill Crump to learn more about this exciting transformation.

Perspective Session - Bringing data back to the business. An MDM survivor's guide

Tony Ellis, Unified Governance Specialist, IBM

During this session Tony will share his own experiences of implementing MDM both as a customer and from his role on the supplier side. Often the challenges are those age-old issues of corporate vision, business buy-in etc. In any organisation being a data centric soul isn’t always easy so it’s important to know that you’re not alone. The good news is that the technology just keeps getting better and better. In this session you’ll also hear about how IBM is making MDM simpler and taking the data closer to the business. It’s an exciting time for MDM and never forget it should always be fun.

· It’s not us it’s them. Why data centric souls must stick together
· Tips and tricks for a successful MDM implementation
· An IBM double whammy. Easier to implement and easier to get data to your business users.

Navigating a New Frontier to Advance TD's Data: OCDO & Finance

Rosemarie Owens-Tunney, AVP, Finance Data Strategy & Management
Mary Munro, Vice President, Data Governance and Communications Office of the Chief Data Officer TD Bank Group

The TD Bank Finance Data Strategy and Management (FDSM) team provides support and Data Governance oversight for 29 Finance Lines of Business and 82 Data Stewards (18 Lead Data Stewards and 64 Data Stewards). FDSM will discuss recommendations and lessons learned to demonstrate a successful, efficient and collaborative approach to meet enterprise policy and standards for all data governance programs including:

• Identifying and resolving data pain points and data issues to align with TD’s data, technology and tool roadmap fostering better access to data, reduced work arounds and improved data quality
• Collaborating with enterprise teams to build a robust data issue and change governance process to resolve issues
• Tactics used to build a collaborative engagement model to integrate and support all data governance activities to achieve optimized enterprise benefits

What You Will Learn:

• Optimize Data Management projects to drive data governance engagement for all programs (Data Quality, Data Lifecycle Management and Metadata Management)
• Engage Finance Data Steward community for success
• Align resolution of data pain points with Finance technology roadmap

Developing and Institutionalising Data Governance - a Case Study at the Western Cape Government of South Africa

Zeenat Ishmail, Chief Director: Provincial Strategic Management Information, Western Cape Government

The Master Plan for Province-wide Data Governance (PWDG) for the Western Cape Government (WCG) of South Africa is a strategic response to the complexity in which Government operates within the area of managing disparate data and application systems.

The Plan is encompassing of the vision for Business Intelligence; an Implementation Roadmap, Solutions Architecture and a Resource Plan. The institutionalisation is done through a three stage approach being conceptualisation and design, pre-implementation and implementation.

The main value is that although it is centrally driven by the Department of the Premier (DotP), the governance arrangements takes a collaborative approach. The establishment of a Data Competency Centre is key to manage the availably, quality, sharing and integrity of data as a strategic asset. The session will map out the first lessons learned of the journey embarked by the WCG to institutionalise data governance for improved performance, efficiency and desired service delivery impact.

What delegates will learn:

• Setting a plan in place to institutionalise data governance
• Getting buy in from the Executive inclusive of Provincial Cabinet
• The establishment of data governance arrangements
• Dealing with the key issues on Data Governance
• Dealing with mandates (roles and functions) and legislation across government
• Speaking a common language (Terminology and Definitions)
• Best practices on Master Data Management
• Data Quality (using a standard quality assurance framework)
• Data Ownership (transparency and openness)
• Collaboration and Governance structures

Field Reports for 'Top 15' Master Data Governance Solutions

Aaron Zornes, Chief Research Officer, The MDM Institute

Master Data Governance is critical to achieving sustainable and effective MDM. Failure to execute Master Data Governance concurrently with an MDM program greatly decreases the probability of success and economic sustainability of MDM programs. Clearly, Master Data Governance is both synergistic and co-dependent with MDM. When deploying MDM, a proper Data Governance (DG) discipline should consider the business drivers, project scope, roles and people filling each role, policies and procedures, data quality, inheritability, social norms, and the business operating model. Moreover, Data Governance is more than a single product or process, rather, it is an ecosystem of products, processes, people, and information. At present, Data Governance for MDM is moving beyond simple stewardship to convergence of task management, workflow, policy management and enforcement.

Understanding the scope, diversity and limitations of current Data Governance solution offerings is tremendously challenging – even more so, given the fast pace of M&A & complexities of integrating such diverse software portfolios. Nonetheless, business and IT leadership chartered with defining and executing MDM programs need help to understand and navigate through the number and variety of DG options.

Through 2018, most enterprises will struggle with enterprise DG while they initially focus on customer, vendor, or product; integrated enterprise-strength DG that includes E2E data lifecycle will remain elusive as most organisations turn to lightweight glossaries with modest Data Steward workflows to support devolved autonomy and multi-disciplinary, bi-modal teams. During 2018-19, the majority of MDM software and service providers will focus on productizing such lightweight DG frameworks while mega MDM software providers will struggle to link governance process with process and data hub technologies. By 2020, mega vendor DG solutions will finally move from “passive-aggressive” mode to “proactive” Data Governance mode.

This session will a review of the current solutions in market as well provide a “top10” list of evaluation criteria for such solutions. Topics include:

• Understanding the “top 10” evaluation criteria for DG solutions — e.g., decision rights management, MDM hub integration, E2E lifecycle management, Big Data & ECM support, DQ/ETL integration capabilities, etc.
• Assessing the vendor landscape— e.g., passive, active, integrated, pro-active, & passive aggressive, etc.
• Determining an enterprise-specific road map to evolve from a siloed, motley collection of DQ tools, processes & point products to a non-obtrusive enterprise DG program (supporting multiple domains, cross-disciplinary teams & federated data management groups)

Business Partner Data “Shareconomy”

Udo Couto Klütz, Robert Bosch
Kai Hüner, Chief Technology Officer, CDQ

To master the numerous challenges of managing customer and vendor data, both at present and in the future, Bosch has teamed up with other multinational companies (among them BASF, Bayer, Nestlé, Novartis, Siemens) to share selected business partner data (e.g. legal names and addresses, tax numbers, or scores to prove the validity of bank accounts) and to collaboratively maintain this data.

The presentation will offer insights as to what challenges a multi-national enterprise such as Bosch encounters in business partner data management, and how these challenges are addressed by a corporate program on strategic, organizational, and system level. It will also outline how cross-corporate collaboration is positioned in this program and what benefits Bosch expects to achieve on a mid- to long-term basis.

Key takeaways of the presentation will be:

• Innovative approach of how to efficiently manage business partner data in a multi-national enterprise
• Insights into a best-practice approach from a global market leader, and
• A set of use cases demonstrating the business value of effective cross-corporate data management

The Anatomy of Sustainable GDPR Compliance

Stijn Waegemans, Inpuls

By now most people have understood that GDPR is not a matter of ticking some boxes and making sure that you end up with a document certifying that “You are now compliant”. The regulation has a profound impact on the way you handle personal information in your organisation. There must be a level of control that assures that all personal information is processed within the boundaries that have been set by the regulation. You might get confused by the regulations requirements that ask you to demonstrate that you understand and govern your personal data use and flows. Consider at Art. 30, the processing register, as an example. You could do a once off high-level documentation exercise but that would be a big waste of resources, given the need for maintaining that information and given the other data subject rights that require a much more detailed insight in the data landscape. To handle this complexity you need to translate the requirements into a structured set of deliverables and metadata model that allows you to sustain a collaborative way of maintaining the metadata. This presentation will explain what is required in terms of metadata for each of the GDPR articles and what relations need to be maintained to support your GDPR initiative.

Attendees will learn:

What metadata is required to support your GDPR approach
How the metadata can be kept up to date
How you can take an iterative approach that goes from high level to detailed metadata
How GDPR metadata links to Master Data Management
What is takes to support consent

Data Governance: A Retrospective

Jon Hill, Executive Director, Data Governance, Nomura

Three years ago Nomura embarked on a large scale data governance programme to ensure compliance with the financial industry’s BCBS 239 regulation and provide a sustainable operating platform for wider business benefits such as advanced automation and digitalisation. BCBS 239 requires banks to have a level of data governance, architecture and data quality management in place for the data used to create key risk metrics and reports.

In this talk Jon will review what went well, what was learned, what should have been done differently, and what puzzles remain. He will focus on:

• Real practical experiences gained from implementing data governance and a data management framework within a global organisation
• The balance and interaction between the human and technology aspects of data governance
• Managing the transition from a compliance programme to a value driven, business-as-usual capability

Maximising Business Outcomes of a Data Governance Programme by Bridging it with Business Performance Management

Dr Andrey Pavlov, Senior Lecturer, Business Performance Management, Cranfield School of Management
Anna Ovchinnikova, Senior Business Analyst, Perfex Lab

What if the logic of Data Governance extended to business performance measurement and strategy execution? In this talk, Dr. Andrey Pavlov and Anna Ovchinnikova present an approach to building a comprehensive business glossary for Data Governance, creating a structure for integrating data management efforts into an organisation’s systems for measuring and managing corporate performance. The speakers will outline the framework for connecting Data Governance with the wider business objectives and present a case study illustrating the application of this logic in the retail industry. This session will explore:

• “What’s wrong with this KPI?”: Performance Measurement meets Data Governance.
• How an extended business glossary from a Data Governance project can be utilised to enhance an organisation’s business performance measurement system.
• From chaotic reporting environment to organised and governed catalogue of performance measures: a case study.

Driving Harmonization of Data in a Challenging Environment

Luca Condosta, Group Finance Vice President, ABB Management Services

ABB is a world leader in the energy industry  and is operating in more than 100 countries and have a double digit number of ERPs (SAP, Oracle and other legacy systems).

A new era has started and the push for simplicity, automation and digitalization is driving the agenda also in the Finance world.

During 2017 an acceleration of this process happened. As Group Finance and Customer-Vendor Master Data domain manager Luca is driving a journey which aims at harmonizing the complexity sometimes through changing the backbones systems, sometimes through mapping tables which will enable central solutions for BI and Analytics.

This is completely changing the rule of the game and the main ingredients are: strong governance, strong knowledge of the cultural differences and trust towards the local units. ABB aims at creating 1 source of truth of their data, leveraging on RPA and syndication to enable business analytics.

Implementing Successful Master Data Governance in a Medium-Sized Multinational Enterprise

Martin Koch, Head Business Applications, SV Group
Dimitri Tombros, Head CC Information Management, AWK Group

The digital transformation of a business catering company is based on better understanding customer needs and providing tailored products. To this end various domains and systems such as CRM, menu management or restaurant POS have to interoperate more closely. Risks regarding the management of sensitive data assets have to be known and managed. An MDM initiative was put in place. In their presentation, SV Group and AWK address the following questions:

• A data asset value and risk-based framework to managing master data has been defined and implemented for a multinational enterprise in restaurant, catering and hotel management business. What are the key elements?
• The initiative, while driven by IT (business application management), needed a substantial involvement and buy-in by business units. How was that achieved?
• Practical methods used to define and implement master data governance instruments and organisational structures. What were the key success factors?
• Martin and Dimitri conclude by summarizing their experiences and lessons learned from the implementation and operation of the defined governance framework.

BT's GDPR Journey ... a Transformational Approach to Personal Data Governance

Mark Hudson, Principal Enterprise Architect, Architecture and Strategy, British Telecom

This case study session outlines the journey BT took in preparing for GDPR. Since its early drafts, BT’s legal and compliance team have been tracking GDPR. It soon became clear that the new law contained more stringent data governance and data protection obligations. Over three years ago, an architectural assessment led to a series of workshop events. Subsequently, an agreed business case included a risk-based investment approach. BT’s GDPR Programme was mobilised and our large IT estate was systematically assessed over a number of months. Initial IT changes were implemented for the information retention and security investment themes. The second phase tackled more complex IT solutions, such as encryption and consent. In parallel, our people training, processes and contracts were revised. The preparations culminated in a renewed data governance and Privacy-by-Design ethos. Post transformation, the challenge now is to maintain and build on our now, heightened data governance approach.

• How to mobilise transformational changes to data governance in large, complex organisations
• Techniques for modelling and prioritising the mitigation of data compliance risk
• Practical hints and tips for identifying cost effective IT solutions that both improve personal data protection and benefit customers

How to implement Data Classification via a Network of Data Stewards

Ahmet Temizsoy, Head of Data Stewardship, Dun&Bradstreet

Data Classification is a critical requirement of any Data Governance Program. At this session, you will hear about how Data Classification was handled at D&B. This will include creation of the policy, as well as enterprise wide implementation as well as key challenges and important next steps. You will also learn about how Data Classification Policy supports Data Handling Standards at D&B, along with the Operating Model for the organization.

What You Will Learn:

• D&B Data Classification Policy & Implementation
• How to make Data Classification reality through a network of Data Stewards
• How to raise Data Classification awareness, and link to Organization’s Security and other Regulatory Requirements.

Skill & Competencies for Data Governance

Chris Bradley, Information Strategist, Data Management Advisors

Are you just starting or are even mid-way through a Data Governance initiative? Undoubtedly, you’ve identified key roles including Data Owner, Steward, Custodian & more.  But what makes a good Owner, what are the skills and competencies required for these (and other) roles.

And it’s not simply the “Information” skills that are essential, but the wider business and soft skills are vital for effective Data Governance roles. This session will:

• Show a capabilities and competencies framework for Data Management professionals
• Describe the key capabilities that are essential for Data Governance role
• Highlight the behaviours and attitudes that Owners, Stewards & Custodians must exhibit to succeed
• Describe the most important Data Governance roles that are required in a successful programme; and
• Discuss if professional Data Governance certification really helps & compare the options

Master Data Change Management

Farah Naili, Master Data BPM, Arriva

Often times in discussions around Master Data, the elements of Change Management are completely overlooked.  Bad data often stems from unclear processes, standards and poor people management.
In this talk, the audience will be given an opportunity to discuss and reflect on the following:

• Questioning process status quo and ownership
• Preparing for people management in change
• Ensuring business continuity & sustainability

Expert Panel: Best Practices in MDM of CUSTOMER Data

Aaron Zornes, Chief Research Officer, The MDM Institute

The ability to deliver a single, trusted, shareable view of customer is universally seen as a key business strategy for commercial and public-sector enterprises. Yet most enterprises struggle to provide even a 90°, let alone a 360°, view of those entities. While historically, many organisations and vendors originally focused on derivatives of CRM, ERP or other vertical industry solutions as their system of record, industry-leading enterprises have since moved on to multi-domain MDM, Big Data/Social MDM and other key augmentations to that original concept. This panel will focus on answers to such questions as:

• Establishing the seeds to grow customer data integration (CDI) — e.g., compliance & risk management; cost optimization & efficiency; cross-sell, up-sell & retention
• Determining the pace to embrace multi-domain MDM, Big Data, Cloud MDM & Social MDM
• Rationalizing an “MDM of CUSTOMER hub” architecture with the reality of multiple ERP, CRM & other MDM hubs

Leveraging GDPR to Embed a Sustainable Data Governance Organisation – A Case Study

Dan Robertson, Chief Data Officer, SSE
Ralf Teschner, Global Data Governance Lead, Capgemini

Most large enterprises have struggled for years with building an effective DG programme. To satisfy GDPR, they’re now developing structures to create data policies and standards, with accountabilities and formalised decision-making processes. This is Data Governance. So why not use this infrastructure and expand it into other data domains such as Product, Supplier, Location, Financial and Asset data? Why not leverage it for other DG interests such as business term definitions, system alignment, data quality, data hierarchies or classification standards?

SSE, the large British electric utility services provider, takes the value of data and the value from data seriously. GDPR focused everyone’s minds on data protection and retention policies, data sharing agreements and unstructured data. But the company looks at Data Governance going wider, with interests far beyond Customer and Employee data.

This joint presentation will also provide real-world examples of how four other large companies in Retail, Utilities and Manufacturing have successfully built a DG programme that is effective, productive and sustainable, that delivers business value and isn’t just geared towards compliance.

• How did SSE build on the GDPR infrastructure to drive business benefits in other areas?
• What made SSE’s DG organisation effective for GDPR purposes, productive for other DG interests, and sustainable for the Business?
• DG/GDPR lessons learned from SSE and other large retail, utility and manufacturing organisations

Where Governance Ends and Business Begins

Dana Julinschi, Master Data Governance & Projects Manager, FrieslandCampina

In 2017, FrieslandCampina finalized the global rollout of their master data governance program. What do they do next? After the excitement and novelty of the first stages wears off, they must keep on working towards ensuring that master data is at a constantly a high quality and an efficient business enabler and that they can become a truly data driven organisation.

In this session, you will find out how to keep your stakeholders engaged in the long run and help them become more self-supporting over time. You will be advised on the way that master data strategy and governance practices must develop in line with how your business evolves and the role that your team has in turning data into valuable insights.

Delegates will learn how to:

• Understand and translate business needs into master data work;
• Use data quality as a stakeholder engagement mechanism;
• Move from “you are the Data Owner” to “I am the Data Owner”;
• Optimise master data capabilities in their organisation.

How Data Governance Delivers a Better (Data) Quality Environment

Nick Keen, National Lead – Data Governance, Environment Agency
Simon Dimbylow, National Lead – Data Quality, Environment Agency

The Environment Agency is a public sector organisation with all of us likely to benefit from their data. In this session Simon and Nick will take you through the EA approach to data governance and data quality and show how they applied this to, and helped resolve a real life problem that could affect many of us at home or at work.

• Explain how they approach data governance in the EA
• How their approach to data governance supports data quality
• The lessons learnt from our DG journey and how to engage with the business

Streamlining Data Management Processes Using Lean Methodology

Gerard Bartley, Manager Global Master Data, Jacobs Douwe Egberts

As a Lean Green Belt, Gerard has been able to apply Lean methodology to his data management processes to drive efficiency and reduce time/cost.

What is Lean? It is a set of techniques to:

• Map out processes
• Identify potential areas of inefficiency (“waste”)
• Deliver process improvements

Whilst originally developed for the automotive industry, many of the Lean techniques can be applied to services such as data management. In effect, from the start of a change request to the end point, we can look at each step of that in turn, each activity, each human touch and see if it can be done better. Lean gives us a set of tools and techniques for analysis and improvement.

Delegates will takeaway:

• An understanding of what Lean is
• Knowledge of techniques to assess processes
• A set of techniques to build improvements

Agile Implementation of an MDM Solution

Helle Lindsted, Master Data Manager, Coloplast A/S

Coloplast is a medtech company developing products and services that make life easier for people with intimate healthcare needs. The main business areas include ostomy care, urology & continence care and wound & skin care.

At Coloplast, the Scrum methodology was chosen for the implementation of an MDM solution. The initial project consisted of five two-week sprints to set up a solution for submission of UDI data for FDA. This presentation describes how they worked and discusses the pros and cons of working in an agile manner for an MDM implementation and our thoughts on future uses of the solution.

The presentation highlights:

• How frequent demos created awareness, interest and excitement among future users
• How stakeholders were actively involved very early in the process resulting in high user satisfaction
• How working hands-on from day one helped the development team understand the capabilities and limits of the solution very quickly

Data Governance Masterclass

Dhivya Venkatachalam, Director, Data Synergie

This session will focus on Data Governance Maturity, on how to successfully steer your data governance organisation from its foundations to a sustainable ecosystem. This workshop is designed to provide you with a robust roadmap and some measures for the next steps in the maturity journey.

As part of the workshop, we will also discuss case studies and success stories. Of what works and what doesn’t. How to identify and engage the different stakeholders, how to successfully build a data governance organisation, record measures and metrics, track your wins, build your data assets and so on.

This workshop helps you start from where you are and take the next steps to move forward. The focus is on the following areas:

• Data Governance Foundations – All the basics
• Building the Data Governance Organisation – To create a sustainable organisation that works
• Getting to a wider audience / Engagement
• Data Governance Maturity
• Roadmap and Next steps
• Measure our success

Successful Implementation of a Master Data Management Programme

Malcolm Chisholm, Chief Innovation Officer, First San Francisco Partners

This workshop focuses on the key elements of an MDM programme that are needed for overall success. It gives practical recommendations while at the same time providing a conceptual understanding of what is involved in these recommendations. Both governance and management are covered, and emphasis is placed in how MDM fits into a larger business strategy and architectural setting. The business needs of master data are described, including strategies for meeting manual and procedural needs. The more technical details are fitted into this framework. MDM programmes are rapidly evolving as new data possibilities emerge and enterprises demand more from MDM than they have previously. These emerging challenges of MDM are addressed in detail, including how MDM supports data scientists and the relationship between Big Data and MDM.

Attendees will learn:

• What Master Data is, how it differs from other classes of data, and what its special needs and challenges are.
• The structure of an MDM programme, including how the business needs to be aligned to data governance and data management within an MDM programme.
• How to deal with integration, semantic, history, quality, and other requirements in an MDM programme.
• MDM architectures, including what tooling can offer, and how these vary with different master data entities.
• The relationship of master data with reference data, and emerging areas of MDM.

"Making It Real" - Establishing the Interdependence of Data Governance and Data Models

Chris Bradley, Data Management Advisors & George McGeachie, Metadata Matters

Data governance is at the heart of all data management activities, and whilst not well understood it is heavily reliant on effective data modelling. Furthermore this is a two-way interdependency – Neither can work effectively without the other.

The role of Data modelling for Data Governance will be shown in this workshop. We’ll describe real-world data governance processes, based upon years of experience with major clients, and the accompanying data modelling practices, and additional information (such as data lineage) required to manage change effectively. Then it’s time for you to put those processes to the test, pushing proposed changes through the data governance pipeline, in which you are a key participant. Will our apparently-perfect processes and data modelling practices cope? Participants will learn from each other as well as from Chris and George.

Delegates will learn:

• The critical role of a data model for data governance
• Common pitfalls in apparently-perfect processes
• The importance of joined-up thinking when implementing data governance and related technology
• The perspective of others involved in the process