There are no formal prerequisites to attend this Dimensional Modelling Foundations Training course.
This Dimensional Modelling Foundations Training is ideal for anyone who wants to gain knowledge of dimensional modelling. However, this will be more beneficial for:
- Data Warehouse Architects
- Data Modellers
- Database Administrators
- Business Analysts
- ETL Application Developers and Designers
- BI Developers and Designers
Dimensional Modelling Foundations Training Course Overview
Dimensional Modelling is a strategy used for efficiently storing data in a data warehouse by combining dimensions and facts. It optimises the database to allow faster data retrieval. Dimensional Models have a certain structure and help organisations to organise data to make performance-enhancing reports. It helps individuals to understand and write queries for making database architecture. Studying Dimensional Modelling Foundations Training course is helpful for learners to gain knowledge of dimensional modelling effectively. This training will help expand skills and prepare learners to build their careers in this vast field.
In this 1-day Dimensional Modelling Foundations Training course, delegates will learn about dimensional modelling of data structures. During this training, they will learn how to create and study enterprise business process lists. They will also learn about the fact table types, identify business processes, conformed dimensions, aggregate navigation, event fact tables, check grain atomicity, and many more. Our highly expert trainer with abundant knowledge will teach the delegates about dimensional modelling concepts and how to use them on their data sets.
It also accommodates the delegates with other related topics, such as:
- E/R modelling
- Conceptual design
- Multiple and separate gains
- Slowly changing dimensions
After attending this Dimensional Modelling Foundations Training course, delegates will be able to identify high-level entities and measures for conformance effectively. They will also be able to identify the metadata to read, analyse, and summarise data for further analysis.