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IRM UK | Data Modelling Essentials
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This 2-day course addresses the core data management topic of data modelling. Often misunderstood and relegated to just the technical aspect of “database design”, data modelling is one of the most important disciplines of data management. The course introduces delegates to data modelling, its purpose, the different types of models, how to construct and read a data model, and the wider use of data models beyond the traditional area of database design.

 Export to Your Calendar 10/5/2020 to 10/6/2020
When: 5 - 6 October 2020
Monday and Tuesday
Where: etc.venues Marble Arch
Garfield House
86 Edgware Rd
London W2 2EA
United Kingdom
Presenter: Chris Bradley
Contact: +44 (0)20 8866 8366

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IRM UK     Data Modelling Essentials         

Use code AEA10 to receive 10% AEA member discount when registering!!

Register On-line:
5 - 6 October, London

Seminar Fee 
£1,295 + VAT (£259) = £1,554


This 2-day course addresses the core data management topic of data modelling.  Often misunderstood and relegated to just the technical aspect of “database design”, data modelling is one of the most important disciplines of data management.  The course introduces delegates to data modelling, its purpose, the different types of models, how to construct and read a data model, and the wider use of data models beyond the traditional area of database design.  It contains a wide-ranging clarification of data modelling concepts and terminology, together with techniques for producing usable data models.

Learning Objectives

This course explains the essential data modelling building blocks. It will help students to understand the differences between relational and dimensional models, and between the different levels of Conceptual, Logical and Physical models.  On completion they will be able to:

  • Describe the purpose of, Conceptual, Logical, and Physical data models
  • Create a Conceptual and a Logical Data model
  • Read and interpret a data model
  • Understand different approaches for fact finding and how to apply normalisation techniques
  • Understand how to validate a data model.

At the end of the course, delegates would have gained the following:

Level Set Understanding & Terminology:

    • Learn about the need for and application of Data Models
    • See the areas where Data modelling adds value to Data Management activities
    • Understand the critical role of Data models in Master Data Management and Data Governance.

Pragmatic Learning

    • Understand the difference between, Conceptual, Logical, Physical and Dimensional Data models
    • Learn the best practices for developing Data models that can be read by humans
    • Through practical examples, learn how to apply techniques in Data modelling

Course Outline

Data Modelling Basics

  • What is Data Modelling and why does it matter
  • What is the relationship between a data model and other types of models in the Enterprise Architecture
  • What is a Conceptual Data model, why it’s important and the pivotal role it plays in all architecture disciplines
  • The major differences between Enterprise, Conceptual, Logical, Physical and Dimensional data models
  • Data vs MetaData; what’s the difference and why does it matter

Data Model Components

  • Data Modelling Basics; Entities, Attributes, Relationships
  • How to identify Entities and Subtypes
  • What are the differences between exclusive and non-exclusive subtypes?
  • How do different data modelling notations represent subtypes?
  • Basic standards that you can use right away
  • Relationships: Cardinality & Optionality, Identifying, Non-identifying, recursive, and many-to-many
  • How does cardinality and referential integrity lead to better data quality?
  • Rules for handling Super types, subtypes, many to many and recursive relationships
  • Keys: Primary, Natural, Surrogate, Alternate, Inverted, Foreign
  • What are the alleged and actual benefits of surrogate keys?
  • Attribute properties & attribute domains

Creating Data Models

  • How to get started with data models
  • What core information is needed to create a data model, how this can be easily communicated to business people, and what visual constructs to use to get their attention
  • Templates and guidelines for a step-by-step approach to implementing a high-level data model in your organization
  • How to capture requirements for data models
  • Approaches for creating a data model (Top Down, Bottom Up, Middle out) and when to use them.

Using Data Models

  • How to use high-level data models to communicate with business people to get the core information you require to build robust applications.
  • The critical role played by Data Models in all disciplines of Information Management.
  • Why Data Models are required for software package implementation
  • Data models are not just for DBMS design, the other areas where models are critical.
  • Maturity assessment to consider the way in which models are utilized in the enterprise and their integration in the System Development Life Cycle (SDLC).

Dimensional Data Modelling Basics

  • Facts and Dimensions, the basics of Dimensional models
  • The key differences between Dimensional & Relational models
  • The use of Dimensional data models in Business Intelligence & Data Warehousing
  • Inmon vs Kimball Data Warehouse approaches
  • How to cater for change in Dimensional models; the different types of slowly changing dimensions
  • Aggregation and Summarisation – what you really need to know
  • Columnar Database & Data warehouse – a forgotten treasure?

Improving your Data Models

  • Data Modelling Notations and tooling
  • Normalisation: 1st, 2nd and 3rd normal form and a brief overview of other normal forms
  • Ten steps for checking the quality of your data models
  • Layout, presenting, and communicating a data model to non-modellers

Who It's For

Practitioners who will need to read, consume or create data models to gain a better understanding of data during Information Management initiatives including:

  • Business Intelligence & Data Warehouse Developers & Architects
  • Data Modellers
  • Data Architects
  • Data Analysts
  • Enterprise Architects
  • Solution Architects
  • Application Architects
  • Information Architects
  • Business Analysts
  • Developers
  • Database Administrators
  • Project / Programme Managers
  • IT Consultants
  • Data Governance Managers
  • Data Quality Managers
  • Information Quality Practitioners



Information Strategist, Data Management Advisors Ltd.

Christopher Bradley has spent 39 years in the forefront of the Information Management field, working for International organisations in Information Management Strategy, Data Governance, Data Quality, Information Assurance, Master Data Management, Metadata Management, Data Warehouse and Business Intelligence.  Chris is an Information Strategist and a recognised thought leader.  He advises clients including, Alinma Bank, American Express, ANZ, British Gas, Bank of England, BP, Celgene, Cigna Insurance, EDP, Emirates NBD, Enterprise Oil, ExxonMobil, GSK, HSBC, NAB, National Grid, Riyad Bank, SABB, SAMA, Saudi NIC, Saudi Aramco, Shell, Statoil, and TOTAL.  He is VP of Professional Development for DAMA-International, the inaugural Fellow of DAMA CDMP, past president of DAMA UK.  He is an author of the DMBoK 2 and author and examiner for professional certifications.  In 2016 Chris received the lifetime achievement award from DAMA International for exceptional services to furthering Data Management education & to the International Data Management community.  Chris guides Global organizations on Information Strategy, Data Governance, Information Management best practice and how organisations can genuinely manage Information as a critical corporate asset.  Frequently he is engaged to evangelise the Information Management and Data Governance message to Executive management, introduce data governance and new business processes for Information Management and to deliver training and mentoring.  Chris is Director of the E&P standards committee “DMBoard”, sits on several International Data Standards committees, teaches at several Master’s Degree University Classes Internationally.  He authored “Data Modelling for the Business”, is a primary author of DMBoK 2.0, a member of the Meta Data Professionals Organisation (MPO) and a holder at “Fellow” level of CDMP and examiner for several professional certifications. Chris is an acknowledged thought leader in Data Governance, author of several papers and books, and an expert judge on the annual Data Governance best practice awards.

DG & MDM Conference Europe 2020 Conference Workshops:

Practical Reference and Master Data Management

Building a Business Aligned Data Strategy

IRM UK Public Courses:

Information Management Fundamentals

Practical Steps for Developing a Business Aligned Data Strategy

Data Modelling Essentials

Mastering Data Modelling Techniques

Register On-line:
5 - 6 October
, London

Seminar Fee
£1,295 + VAT (£259) = £1,554

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