What this book covers

Chapter 1, Data Warehouse Design, explains the first steps in thinking and designing a BI system. As the first steps, a developer needs to design the data warehouse (DW) and needs an understanding of the key concepts of the design and methodologies to create the data warehouse.

Chapter 2, SQL Server Analysis Services Multidimensional Cube Development, explains how an OLAP multidimensional structure is required to provide fast query response and aggregated data from a data warehouse. In this chapter, readers will learn what OLAP provides and how to design OLAP with Microsoft SSAS Multidimensional.

Chapter 3, Tabular Model Development of SQL Server Analysis Services, explains that SSAS Tabular is a new method of presenting data in Microsoft BI 2012 and is very useful in small BI systems and when a developer wants to create POC. In this chapter, the reader will learn about SSAS Tabular and how to use it in BI projects.

Chapter 4, ETL with Integration Services, describes how ETL is an operation of transferring and integrating data from source systems into the data warehouse. ETL needs to be done on a scheduled basis. In this chapter, readers learn how to think about ETL processes and use SSIS to perform data transfers.

Chapter 5, Master Data Management, guides readers on how to manage reference data. Master Data Management (MDM) is very critical in all integrated systems, especially in BI and data warehouse. In this chapter, the reader will learn how to use Master Data Services (MDS) to implement an MDM solution.

Chapter 6, Data Quality and Data Cleansing, explains that data quality is one of the biggest concerns of database systems. The data should be cleansed to be reliable through the data warehouse. In this chapter, readers will learn about data cleansing and how to use Data Quality Services (DQS), which is one of the new services of SQL Server 2012, to apply data cleansing on data warehouse.

Chapter 7, Data Mining – Descriptive Models in SSAS, provides a descriptive model on historical events. In this chapter, readers will understand data mining concepts and how to use data mining algorithms to understand the relationship between historical data, and how to analyze it using Microsoft technologies.

Chapter 8, Identifying Data Patterns – Predictive Models in SSAS, focuses on predicting future outcomes based on a pattern recognized in the existing data. In this chapter, readers will become familiar with algorithms that help in prediction, and how to use them and customize them with parameters. Users will also understand how to compare models together to find the best algorithm for the case.

Chapter 9, Reporting Services, explores Reporting Services, one of the key tools of the Microsoft BI toolset, which provides different types of reports with charts and grouping options. In this chapter, readers will learn when and how to use SSRS to create and design reports from data warehouses, SSAS Multidimensional, or SSAS Tabular.

Chapter 10, Dashboard Design, describes how dashboards are one of the most popular and useful methods of visualizing data. In this chapter, readers will learn when to use dashboards, how to visualize data with dashboards, and how to use PerformancePoint and Power View to create dashboards.

Chapter 11, Power BI, explains how predesigned reports and dashboards are good for business users, but power users require more flexibility. Power BI is a new self-service BI tool. In this chapter, you will learn about Power Query as a self-service ETL tool and Power Map as a 3D geospatial data visualization tool.

Chapter 12, Integrating Reports in Applications, begins with the premise that reports and dashboards are always required in custom applications. This chapter explains different ways to integrate SSRS reports and other dashboards into C# or VB.NET applications in web or Metro applications to provide reports on the application side for the users.