Data Modelling for Data Analysts

DATA MODELLING

• What is Data Modelling? 

• Introduction to Relational Databases

• A crash course in SQL

• Relationships and Relationship types

• Creating "lookup tables" to aid with the analysis of data

• An Introduction to Entity Relationship Modelling

• Conceptual, Logical and Physical data models

• Transactional Data Modeling vs Analytical Data Modeling

  • How transactional databases typically evolve

  • Designing a Data Warehouse

  • Online Transaction Processing (OLTP) vs Online Analytical Processing (OLAP) databases

  • Why do we need to architect each one differently?

  • Normalising vs Denormalising Data

  • Star and Snowflake schemas

  • Performance considerations when searching relational database tables

• An Introduction to NoSQL Databases

• An Introduction to Hadoop

• Data Lakes, Data Warehouses and Data Marts 

• Data Warehouse Architecture

  • The Inmon method for designing a Data Warehouse (top-down approach)

  • The Kimbal Method for designing a Data Warehouse (bottom-up approach)

  • Breaking the rules with NoSQL and Hadoop.

WORKSHOPS 

• Students will be given a range of data sources to model and analyse using both the Kimball and Inmon approach to data modelling. 

• Data will be visualised using their tool of choice - Excel, Power BI, Qlik or Tableau