Data Modeling Master Class The Master Class is a complete data modelling course, containing 3 days of practical techniques for producing conceptual, logical, and physical relational and dimensional and NoSQL data models. After learning the styles and steps in capturing and modelling requirements, you will apply the best practices approach to building and validating data models through the Data Model Scorecard®. You will know not just how to build a data model, but how to create a data model well. Two case studies and many exercises reinforce the material and will enable you to apply these techniques in your current projects.
Top 10 Objectives
- Explain data modelling components and identify them on your projects by following a question-driven approach
- Demonstrate reading a data model of any size and complexity with the same confidence as reading a book
- Validate any data model with key “settings” (scope, abstraction, time frame, function, and format) as well as through the Data Model Scorecard®
- Apply requirements elicitation techniques including interviewing, artefact analysis, prototyping, and job shadowing
- Build relational and dimensional conceptual and logical data models, and know the tradeoffs on the physical side for both RDBMS and NoSQL solutions
- Practice finding structural soundness issues and standards violations
- Recognise when to use abstraction and where patterns and industry data models can give us a great head start
- Use a series of templates for capturing and validating requirements, and for data profiling
- Evaluate definitions for clarity, completeness, and correctness
- Leverage the Data Vault and enterprise data model for a successful enterprise architecture
This workshop focussed on the Data Modelling discipline within Data Management concerned with discovering, analysing, and documenting the concepts, relationships, constraints, and operations on data. It created a bridge for the non-technical, who isn’t going to be the one creating the agency-wide data models, having an understanding of the basic concepts help both data analysts and the business achieve the best results from data.
Steve Hoberman’s explains why data modelling is so important to understanding data and application development in his video.
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