Pre-Conference Workshops - 18 May 2015
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 firsthand 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
Intelligent Business Strategies
This workshop focusses looks at 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 address design issues such as inbound integration of master data to consolidate master data when it is scattered across many different data sources, and the outbound synchronization of it to supply both operational and analytical systems. It also looks at master data virtualization 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 synchronization to achieve best practice in design and implementation. The session covers the following
- An introduction to data governance
- Introducing a shared business vocabulary
- Metadata management
- Enterprise data quality and data integration
- 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 standardizing inbound data to a an MDM system
- Should history be kept in a MDM system?
- Approaches to cleansing, and matching
- Consolidation Vs virtualizing master data to create an MDM system
- Best practices in designing outbound master data synchronization
- Integrating an MDM system with an enterprise service bus for outbound synchronization of operational systems
- Schema and integrity synchronisation problems that can occur and what to do about them
- Conflict resolution on outbound synchronization
- Design considerations when integrating MDM with ETL tools for synchronizing data warehouses and data marts
- Maximising the use of data virtualization in MDM
- The implications of switching to centralized master data entry
- The change management program imposed by centralized master data entry
Chief Data Officer
FromHereOn and DAMA UK
This workshop covers an overview of the process, tips and techniques of successful CDMP exam taking. In this interactive and informative session, you will learn:
- What is the CDMP certification process
- The DAMA-DMBOK & CDMP data exams alignment
- What topics comprise each exam’s body of knowledge
- Concepts and terms used in the CDMP exams
- A Self-assessment of your knowledge and skill through taking the sample exams.
VERY IMPORTANT: You will need to bring your own unencrypted Windows-based laptops – exams run off the USB drive. Your test (and live) exam results and performance profile can be viewed immediately.
Attendees of the half day workshop will also receive some refresher tuition covering several of the most common topics seen in recent examinations. Note however this is not a substitute for past experience and education. In the afternoon there will be three 90 minute exam sessions. The schedule for the day will be as follows:
09:30-12:45: Workshop Preparation for the Certified Data Management Professional (CDMP) Exams
13:30-15:00: Exam 1
15:30-17:00: Exam 2
17:30-19:00: Exam 3
Workshop attendees will take the certification exams on a "pay if you pass" basis (passing is 50% or better). If you take and pass all three certification exams, you would leave MDM/DG 2015 with a CDMP credential. Cost is $285 per exam.
- 3 * 90 minute examination sessions (in the afternoon).
- Each exam is 90 minutes in length and has 110 multi-choice questions
- Your score is immediately known after exam is taken
- Exam fees for DMIQ attendees are ‘pay if you pass’ ($285 each exam) for this class session.
- Passing at Practitioner level requires 50% or higher in all 3 exams, “Master” level is attained by passing all 3 exams at 70% or greater.
EPI-USE & DAMA International
Data Governance Programs often seem to start with failure as a foregone conclusion. Horror stories from other organisations and data professionals permeate the industry
Having been a big part of the implementation and maintenance of a successful DG program at a large Southern African Telco, Sue will focus on the practicalities, how to turn the theory into practice and how to make it stick. Having a number of years experience in practical Data Governance, the next logical step is for Sue to take various themes and issues raised during her work and get the group working on the practical pieces that are needed to start your Data Governance Journey. If you are a beginner in DG and are looking for a framework or some practical hand-holding this is the ideal workshop. If you are already working on DG but feel like you are wallowing, then this workshop will help you focus on what you need to do next. You will walk away with a much better understanding of what you are going to be doing, together with various documents that you have helped craft in this workshop. Each part of the agenda has one or more exercise sessions.
- Starting Up
- Identifying Stuff To Do
- The Fun Part
- What went wrong and how did we fix it? – the practical know-how of implementing DG
“Information asset” needs to be more than a metaphor; you need to provide actionable measures to demonstrate that your data programs are working. So you are told to measure your IM and DG program’s progress and value. But how do you do that? Where is the data? What are the metrics that work? This session will review what types of metrics are suitable for measuring the success of your IM or DG program. A case study will be used to show how metrics can be created for any type of company or organization. Attendees will learn techniques to start to manage information as an actual enterprise asset, and considerations for quantifying the value and progress of information management. Topics to be covered include:
- What types of metrics are there? There is a lot more to measuring value than common ROI
- What categories of metrics are there? You need to measure people and technology as well as processes.
- How do we assemble and use metrics? Even if you had them, do you know what to do with them?
- Where do I get the data? The data is out there – you need to be creative.
For a very long time, the common denominators of decision making and data modelling have been data supply and data quality aspects. Data modelling has been used widely when building business intelligence solutions, establishing systems integration, and building data sourcing solutions. But it does not end there anymore. Now, there is a new discipline called Decision Intelligence that can take experienced data models into completely new contexts. Rather than simply providing facts and figures, leaving the interpretation to the decision maker, Decision Intelligence is a way to understand how today’s decisions impact future outcomes, under a given set of conditions. It uses decision model diagrams to show how decisions impacts key parts of your organization, leading ultimately to outcomes of interest. Decision Intelligence does not rely on large data volumes or high data quality. It can rely also on small data and great knowledge. Designing decision models is not equivalent to data modelling. But having profound Conceptual Data Modelling knowledge is an excellent base for such design.
What you will learn:
- What is Decision Intelligence (DI), how is it performed and how do we use it?
- Basic elements of a decision model
- How to design a decision model
- How to implement and execute a decision model
Effective Data Quality Management sits at
the heart of every successful Data Governance programme. And yet, the topic of
data quality is still misunderstood by many – a situation compounded by the use
of unfamiliar jargon and too much emphasis on technology.
This half-day workshop will bring Data Quality Management into focus, dispel the myths and equip Data Governance practitioners with the essential understanding they require. With plenty of practical advice on how to avoid the common pitfalls, both beginners and those already familiar with the topic will learn how to use the benefits of Data Quality Management as the fuel to drive forward their Data Governance initiatives.
The workshop will be structured around 4 key topics:
- The Truth About Data Quality
- Monitoring Data Quality
- Improving Data Quality
- Using Data Quality to Drive Data Governance
The oft-quoted verse “For the want of a nail, the shoe was lost” highlights how seemingly small things can have an outsized impact. In the contemporary enterprise, no “small thing” is as important or as frequently overlooked as the reference data that is used to provide the fundamental classifications that are foundational to operational efficiency, risk data aggregation, and reporting. In this workshop, the focus will be on the scope of reference data in the enterprise, the criticality of effectively governing shared reference data as an enterprise asset, and the impact of RDM software as used to provide effective governance and control of enterprise reference data – including business glossary, authoring, workflow, versioning, and hierarchy management capabilities. Topics to be covered will includes case studies which illustrate:
- Defining reference data & why it is foundational to both operational & analytical MDM initiatives
- Understanding why RDM is the ideal place to begin your MDM Journey
- Determining what the key requirements for an RDM solution should be
The Data Governance Coach
Data governance is getting a reputation for being complex and extremely challenging to implement, but it need not be. Learn from others experiences and do not repeat their mistakes. Join Nicola Askham, The Data Governance Coach, to learn about the many pitfalls that you could face, how you can deal with them and more importantly avoid altogether if you take a structured approach to your data governance initiative.
Join this session to learn:
- What not to do in your data governance initiative
- What to do to overcome some of the common challenges
- Tips and best practice advice to make your data governance initiative successful
This workshop is not just for CDOs! Chief Data Officer, EVP of Information, Head of Informatics, Data Scientist are several of the many titles popping up as labels for the “top data job” within an organization. As varied as the individual companies and business challenges can be, they all have distinctly similar challenges and approaches. Everyone in the data world can benefit from learning their tactics, philosophies and success stories. This workshop will review the success factors and approaches of many data leaders.
- Selling and Sustaining Data Management
- Staffing and Organization Design
- Rules of being a business partner, not an order-taker
- How the CDO interfaces with other functions
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, 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 organisations. 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
One of the main information governance challenges is trying to properly position it within an organisation and more importantly define the interaction with other disciplines that are already established in an organisation. Most organisations are faced with each information related discipline trying to solve the puzzle in their own unique way. Each approach might make sense, but stop short answering the real question how all of this fits together. There are many working models for information governance defined but we have no industry consensus on terms such as data steward or owner. During this session Jan will propose a working model that is able to cover the core information governance activities and that allows you to establish information governance in your own organisation.
- Fundamental tasks and roles in information governance
- How do we position information governance, data management, BI, quality, enterprise architecture, risk and data science?
- Comparing COBIT 5, Mike 2.0 TOGAF and DMBOK
- Applying the roles to your organisation
- Enabling the change
- Transforming from program to recurrent mode
- Linking the governance roles to other disciplines
- Defining the objectives and formal deliverables allowing you to interact with the other organisational components.
We are in the era of Big Data wherein technologies can now support a wide variety of data at seemingly infinite data volumes at real-time velocity. Yet MDM tools and technologies remain relatively unchanged in the 10 years since companies began deploying such solutions. Some might say that MDM itself has turned into the very silo it was designed to circumvent. Granted, certain solution providers now offer MDM in the cloud to enable smaller companies to benefit from MDM at a much lower ongoing cost, but for most enterprises that isn’t enough to meet increasing business demands.
Today’s end-users want access to a complete view – not just of customers or products – but rather a blended view of all master data entities plus transaction, interaction and social data. And they want their information delivered in the form of LinkedIn/Facebook style data-driven applications. They also want faster time-to-value and expect a new breed of enterprise data-driven applications that include reliable data, relevant insights and recommended actions.
In this workshop, one of the pioneers in the next-generation of MDM solutions will share best practices, case studies and technology considerations by discussing these topics and more:
- Leveraging enterprise multi-channel data to enable ‘inside-out’ client view via MDM
- Understanding the business value of Big Data, NoSQL vs. RDBMS vs. Data Warehouse, Hadoop (HDFS & MapReduce)
- Establishing the business case for MDM & real-time data-driven applications (a case study)
17:30-18:00 - Afternoon Lightning Talks
Lightning Talks given straight after each other - 5 minutes - 6 speakers/subjects
A light hearted and fun session.