Course Practical data modelling

virtual

Data Modelling course tile

Data Modelling is the sharpest scope management tool available to information systems development.

  • Virtual
  • 4 x 4 hour session
  • This course runs on an as required basis

A$1900 +gst

REGISTER INTEREST
buy now

Need this course for your whole team? Try our Business solutions

Download brochure

Practical Data Modelling

Data modelling is not optional; no database was ever built without at least an implicit model

Level 2

  • 4 live instructor sessions
  • Hard copy workbook
  • Case study videos
  • Certificate of completion

Course objectives

On completion of this course, you will be able to:

  • Articulate why data modelling is important
  • Recognise the difference between a process model and a data model
  • Recognise the different levels of abstraction of data model
  • Build a data model

Benefits of this course

Gives you confidence to:

  • Understand what a data model is saying
  • Ask questions about a data model and its content
  • Recognise if your data requirements are captured
  • See how business data is implemented in technical solutions

Who is this course for?

It is targeted at anyone working in data requirements specification, data modelling or those working extensively with data modelling professionals and wish to be able to develop and review at more than just a basic level.

Why Data Training?

  • Organisations mandate training to protect valued assets: People, Money, Reputation and Data
  • Helps staff Improve their understanding and confidence in handling data assets.
  • “Organisations rely on their data assets to make more effective decisions and to operate more efficiently” (DMBoK V2 P20)

Course content

The course contains 2 sections:

  • An introduction to data modelling
  • Practical data modelling
data management

An introduction to data modelling

The course teaches:

  • How to read data models
  • Modelling from primary sources

What to look for Rich in case studies the course also covers the areas of:

  • Introduction to Relational modelling
  • Removing redundancy through normalisation
  • Entity Modelling
  • Attribute modelling including data types, value range & codes
  • Development of attributed conceptual models
  • Practical development of a data model utilising example scenarios
data governance

Practical data modelling

The course expands on section 1 content with:

  • More sophisticated modelling techniques
  • Practical warehouse/lake modelling
  • Larger case studies

The course also covers the areas of:

  • Subtypes & Supertypes
  • Roles
  • Time & History
  • Nulls, optional and completeness
  • Types of identifiers (keys)
  • De-normalisation
  • Reuse, patterns & resources
  • Data warehousing modelling (Star Schemes and an introduction to Vault models)
  • Bringing together a number of skills by solving a specific tangible large case study
  • No SQL considerations.