Introduction to Business Intelligence

This course will introduce the key concepts of business intelligence, data integration, data warehousing, data virtualisation and data mining through a case study of a fictitious retail company, consisting of multiple branches, that aims to consolidate its view of the business, establish a consistent way of reporting on key performance indicators, and gain a competitive advantage by leveraging the power of data integration and analysis.

You will have the opportunity to learn to use the Microsoft Business Intelligence suite of tools (SQL Server, SSAS, SSIS, SSRS, Excel PowerPivot and Excel Data Mining) and Tableau.

Session 1

Definitions, Concepts, Architecture, and Tools for Data Warehousing (DW) and Data Virtualisation (DV)

An overview of the motivation for adopting DW, the difference between DW and a traditional database, the applications of DW, the characteristics of DW, the major DW solution providers, Data virtualisation, etc.

Session 2

DW Design and Dimensional Modelling

An overview of the DW development life-cycle and in particular the Design phase.A hands-on practical session to build a data warehouse and its underlying dimensional model (dimensions and cube) using Microsoft SQL Server Analysis Services (SSAS).

Session 3

Data Integration: Extract, Transform and Load (ETL)

An overview of how data from multiple data sources (e.g., Excel spreadsheets, text files, various databases, etc.) can be pulled together in a single DW.A hands-on practical session to build a data integration solution using Microsoft SQL Server Integration Services (SSIS).

Session 4

Data Analytics using SQL/OLAP and MDX (Multi-Dimensional eXpressions)

An overview of how analysts can leverage the power of data analytics using their preferred tools (e.g., Excel or Tableau) or using query languages such as SQL and MDX.

Session 5

KPIs (Key Performance Indicators) and Dashboards

An introduction to the design and use of KPIs in Microsoft SSAS and Excel, as well as the design of reports in Microsoft SSRS.

Session 6

Data Mining Techniques and Applications

An overview of the use of data mining techniques on real-life applications (shopping basket analysis, forecasting, clustering, etc.) using Microsoft SSAS and Excel.

The key concepts will be delivered via short lectures to give you the opportunity to spend most of the time applying your learning via hands-on interactive labs.

The same case study will be used throughout the duration of the course to give you a consistent experience of the entire BI lifecycle.