Book Image

PowerPivot for Advanced Reporting and Dashboards

By : Robert Bosco J
Book Image

PowerPivot for Advanced Reporting and Dashboards

By: Robert Bosco J

Overview of this book

<p>Business intelligence technology gives an organization the power to make decisions using large volumes of data. By obtaining an adequate amount of data and integrating data from a variety of sources, a user can get a comprehensive knowledge of their business and business strategies. PowerPivot is a free add-in to the 2010 version of the spreadsheet application MS Excel. It extends the capabilities of the PivotTable data summarization and cross-tabulation feature with new features such as expanded data capacity, advanced calculations, the ability to import data from multiple sources, and the ability to publish workbooks as interactive web applications.</p> <p>PowerPivot for Advanced Reporting and Dashboards will teach you the fundamentals of PowerPivot as well as how to use the different data types available. This book also discusses useful tips and tricks for handling and resolving errors that might pop up while creating your report. With this book, you will be able to create relevant BI reports quickly and efficiently.</p> <p>Moving on from the basics, this book will explain the types of data sources that can be imported into PowerPivot. You will then delve into relationships, hierarchies, and data model creation using imported data. You will also learn how to employ DAX functions to transform unstructured data into structured data. Finally, this book will teach you how to create reports such as Pivot Tables, Pivot Charts, Slicers, KPIs, and Perspective reports using PowerPivot and how to publish them using the SharePoint server.</p>
Table of Contents (12 chapters)

General overview of a data model


It provides decisional information at an organizational level from integrated and aggregated data, and gives users an intuitive and manageable view of information. A Data Model creates a new repository that integrates data from various sources and then makes the data available for analysis and evaluation aimed at decision-making processes.

A data model should generally be used for analysis. For general analysis, a data model should be or is generally expected to be:

  • Homogenized

  • Integrated

  • Prepared

  • Detailed and aggregated

The logical design of a data warehouse is based on principles that are different from those used in operational databases as there are issues such as data redundancy and denormalization with relations. Denormalization is the process of integrating multiple small tables into one big table in which there are data redundancy issues, but it is deliberately designed for the data model since it speeds up the query performance. Normalization is the reverse...