Star schema and Data Vault techniques are very important when designing data structures for a data warehouse and data marts. This course covers this matter in detail. The course also pays attention to modern developments.

During this course you will learn:

• how to design a data structure using a star schema;
• how to deal with history in a dimensional model;
• modern insights in data modelling.

• Star schemes:

  What is dimensional modelling? • Why a star scheme? • relational versus multidimensional databases • facts table, dimension tables • dimensions: causal, heterogeneous, monster, mini, degenerated • normalisation, denormalisation, snowflake schemes • pure star scheme versus snapshot.

• History in a data warehouse:

  Detail versus analytic attributes • mutations in dimensions, type 0 to 5 approach • minidimensions and history • transaction orientation versus state orientation • scheme changes through time

• The OASI concept:

  The One Attribute Set Interface • technical versus user dimensions • join navigation, aggregate navigation • OASI and heterogeneous dimensions

• Design, starfinding:

  DWH-Blueprint, evolutionary development • conform dimensions • sample - snapshot - adapting a star scheme • OLAP design • approach for dimensional modelling • starfinding

• Advanced concepts:

  Bridge tables • complex hierarchies • star schemes and meta-data • extraction, cleansing, transformation and loading

• User disclosure:

  Middleware • protection against 'runaway' queries • OLAP tools • report tools

The theory will be illustrated by exercises. As the number of attendees is limited, all students will be individually coached during these exercises. Furthermore, an extra instructor will be present when needed. In this way, everyone will get optimal benefit from this course, even if there are differences in the background of the students.

Delivered as a live, interactive training: available in-person or online, or in a hybrid format. Training can be implemented in English, Dutch, or French.

Basic understanding of relational database systems is required (see SQL and relational databases fundamentals).

Designers of data warehouses.