Business Intelligence (BI) and Data Warehouse – Introduction
Business Intelligence (BI) is the key to structured preparation and efficient analysis of complex business data. The core element of this concept is the Data Warehouse (DWH); it collects data, processes it and prepares it for specific target groups..
The course will cover the basics of the Data Warehouse concept. The various aspects of data provision (ETL), right through to collection and data management necessary for analysis of separate datasets (Data Marts) are discussed. The course will consist of practical exercises to help participants apply their knowledge.
At the end of the course, you will be able to actively collaborate in a BI project. You will learn the basic concept and purpose of a DWH and the terms associated with it. You will learn the various requirements for analysis/transaction systems and understand the principles of multi-dimensional data analysis. You will also be able to use the central modeling pattern and the methods and processesfor modeling BI systems.
Course contents/Methodology/Target group
- Purpose of a DWH
- Historical development of information systems
- DWH architecture
- Online Analytical Processing (OLAP)
- Selecting analysis and transaction systems
- Dimension, member, fact, hierarchies in dimensions
- OLAP operations (Slicing, Dicing, Roll-Up, Drill-Down etc.)
- Data Mart
- Modeling technique Star Schema
- Star Schema variations (Snowflake, Galaxy)
- Fact types
- OLAP storage concepts (ROLAP, MOLAP, HOLAP)
- BI modeling method
- Advantages of modeling in BI
Project managers, business department employees, analysts, management consultant
Helpful: Basic data modeling terms
Model-based Business Intelligence (BI) and Data Warehouse (DWH) Modeling
In this course you will learn various aspects of a BI and be able to differentiate between BI modeling elements and apply them correctly.