Business-Oriented Data Modelling Masterclass: Balancing Engagement, Agility, and Complexity. 3.5 hours x 5 days Virtual Course.
Speaker: Alec Sharp
5-9 December 2022
All public courses are available as in-house training. Contact us for more information.
Overview
Virtual Course
Please note that this course consists of 3.5 hours x 5 days (13:00 – 16:30 GMT)
This workshop is suitable for both new and experienced modellers. It first explores unique techniques for rapidly developing high-quality models while maintaining the involvement of business professionals. It then provides hands-on practice with skills in more challenging topics – generalisation, recursion, subtyping, modelling time and history, presenting models to non-technical groups, the connection between E-R modelling and dimensional modelling, and many more. In all cases, the underlying philosophy is that a data model is a description of a business, not of a database.
Three main themes are explored in a very practical way:
- The foundations of data modelling – what a data model really is, and maximising its relevance
- The human side of data modelling – improving communication skills and engaging the business
- The complex side of data modelling – getting better at modelling difficult situations
Pre-requisites: None, although an understanding of information systems concepts may be helpful.
All public courses are available as in-house training. Contact us for more information.
Learning Objectives
On workshop completion, participants will be able to:
- Apply techniques that engage business professionals in developing a concept model / conceptual data model;
- Use entity-relationship modelling to depict entities, facts, and rules at three levels of modelling – contextual, conceptual, and logical models;
- Utilise the three “learning modes” in developing and presenting a model – Visual, Auditory, and Kinesthetic;
- Apply event analysis and other techniques to discover and meet additional requirements;
- Use subtyping, recursion, multi-way associations, and other structures to model difficult rules;
- Model change, correction, and time-dependent business rules with “temporal data models”;
- Rapidly develop a first-cut dimensional model from a well-structured ER model;
- Prepare and deliver a data model review presentation to a non-technical audience.
Course Outline
- Essentials of Data Modelling
- What really is a data model or concept model?
- Essential components – entities, relationships, attributes, and rules
- Hands-on case study – how data modelling resolved business issues, and supported other business analysis techniques
- Guidelines for comprehension – how to lay out Entity-Relationship Diagrams (“ERDs”)
- The narrative parts of a data model – definitions and assertions
- Group exercise – getting started on a data model, then refining it
- Common misconceptions about data models and data modelling
- The real purpose of a data model
- Contextual, Conceptual, and Logical Data Models – purpose, audience, definition, and examples
- Overview of a three-phase methodology for developing a data model
- Establishing the initial conceptual data model
- Top down vs. bottom up approaches to beginning a data model – when is each appropriate?
- A bottom-up approach focusing on collecting and analyzing terminology
- A structure for sorting terms and discovering entities
- Exercise – developing an initial conceptual data model
- Entities – what they are and are not
- Guidelines for naming and defining entities
- Three questions to help you quickly develop clear, useful entity definitions
- Exercise – identifying flawed entities
- Six criteria that entities must satisfy, and four common errors in identifying entities
- Identifying relationships
- Fundamental vs. irrelevant or transitive relationships
- Good and bad relationship names
- Multiplicity or cardinality – 1:1, 1:M, and M:M relationships, and useful facts about each
- Common errors and special cases – recursive, multiple, and supertype-subtype relationships
- Attributes – guidelines and types
- Attributes in conceptual models vs. logical models
- Developing the initial logical data model by adding rigor, structure, and detail
- Transition to the logical model – shifting the focus from entities to attributes
- Multi-valued, redundant, and constrained attributes, with simple patterns for dealing with each
- An understandable guide to normalisation – first, second, and third normal forms
- Higher order (fourth and fifth) and Boyce-Codd normal forms
- Exercise – developing the initial logical data model
- Four types of entities – kernel, characteristic, associative, and reference
- Guidelines and patterns for dealing with each type of entity
- How to draw your E-R Diagram for maximum readability and correctness
- Optional and mandatory relationships
- Considering time and history when looking at relationships
- Typical attribute documentation
- A common source of confusion and disagreement – primary keys
- What primary keys are, what they’re really for, and three essential criteria
- The four Ds of data modelling – definition, dependency, detail, and demonstration
- E-R Diagramming – symbol sets and their problems, rules for readability and comprehension
- Correctly handling attributes
- Granularity – dealing with non-atomic and semantically overloaded attributes
- Dealing with reference data and the “types vs. instances” problem
- Three attributes that always need a qualifier
- Vector modelling – entity or attribute?
- Interesting structures – generalisation, recursion, and the two together
- Generalisation (subtyping) – when to use it, and when not to
- Generalisation with and without specification
- Guidelines for using recursive relationships
- Generalisation and recursion working hand-in-hand as a cure for literalism
- Recognizing lists, trees, and networks, and modelling them with recursive relationships
- Modelling difficult rules by combining generalisation (subtyping) and recursion
- Staying clear on generalisation vs. roles, states, and aggregation
- Modelling time, history, and time-dependent business rules
- Historical vs. audit data, and when to show them on a data model
- Thanks, Sarbanes-Oxley! Why we need “as-of reporting” and how to model data corrections
- “Do you need history?” – how to tell when your client is misleading you
- Modelling time – special considerations for recording past, present, and future values
- Four variations on capturing history in a data model
- Seven questions you should always ask when a date range appears
- Modelling rules on relationships and associations
- Using multi-way associations to handle complex rules
- “Use your words” – how assertions, scenarios, and other techniques will improve your modelling
- Associative entities – circular relationships, shared parentage, and other issues
- Alternatives for modelling constraints across relationships
- Advanced normal forms – how to quickly recognize potential 4NF and 5NF issues
- A simpler view – why the five normal forms could be reduced to three
- Preparing and delivering a data model review presentation
- Context – your audience, and why the model matters to them
- It’s a story, not a data model! Building a storyboard
- Five key techniques for presenting data models or other technical subjects
- The mechanics of the data model review presentation
- A demonstration
- Bridging the “E-R vs. Dimensional” divide – the world’s shortest courseon dimensional modelling
- The perils of dimensional modelling without understanding the underlying E-R model
- Spotting facts and dimensions – the relationship between dimensional models and E-R models
- Saving time – building a first-cut dimensional model from an ER model
Who It's For
Roles that are currently benefitting from this workshop include:
- Specialist data modellers, data architects, data analysts, and DBAs who wish to hone their skills.
- Business analysts, business architects, enterprise architects, and application architects
- Application / solution developers (especially on Agile teams)
- Business professionals, Subject Matter Experts, and Project / Programme Managers involved in the analysis, design, and development (or selection and configuration) of a system.
- BI (Business Intelligence) professionals, DW (Data Warehouse) professionals, big data specialists, data scientists, analytics specialists, and data lake implementers
Speaker
Alec Sharp
Senior Consultant
Clariteq Systems Consulting
With almost forty years of consulting experience, Alec Sharp has provided analysis, architecture, and business change expertise around the world. He has also delivered hundreds of top-rated presentations at international conferences, always based on real-life experience. These include “Getting Traction for Process – What the Experts Forget,” “The Multi-Skilled Influencer – Becoming a T-Shaped Professional,” and “Days not Weeks or Months – Process Change in Agile Timeframes.” Alec’s 90-minute briefing “Five Things You Need to Know About Business Processes” has been delivered to senior executives at major organisations around the globe. His book “Workflow Modelling” is a consistent best seller in the Business Process Change field and is widely used as an MBA text and consulting guide. He was awarded DAMA’s Professional Achievement Award, a global award given to one professional a year for contributions to the Data Management profession.
Fees
- 3.5 days
- £1,195
- £1195 + VAT = £1434 (Price if you book by 16th May)
- 3.5 days
- £1,295
- £1,295 +VAT = £1,554 (Price if you book after 16th May)
Group Booking Discounts
Delegates | |
---|---|
2-3 | 10% discount |
4-5 | 20% discount |
6+ | 25% discount |
Cancellation Policy:
Cancellations must be received in writing at least two weeks before the commencement of the seminar and will be subject to a 10% administration fee. It is regretted that cancellations received within two weeks of the seminar date will be liable for the full seminar fee. Substitutions can be made at any time.
Cancellation Liability:
In the unlikely event of cancellation of the seminar for any reason, IRM UK’s liability is limited to the return of the registration fee only. It may be necessary, for reasons beyond the control of IRM UK, to change the content, timings, speakers and date of the seminar.