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Professional Microsoft PowerPivot for Excel and SharePoint

作者: ebook

ISBN: 0470587377

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Professional Microsoft PowerPivot for Excel and SharePoint

Date: 2010
Pages: 384
ISBN-10: 0470587377
ISBN-13: 978-0470587379
ASIN: undefined
Author: Sivakumar Harinath ,Ron Pihlgren, Visit Amazon's Denny Guang-Yeu Lee Page

Size: 25 MB
Format: pdf
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With PowerPivot, Microsoft brings the power of Microsoft's businessintelligence tools to Excel and SharePoint users. Self-servicebusiness intelligence today augments traditional BI methods,allowing faster response time and greater flexibility. If you're abusiness decision-maker who uses Microsoft Office or an ITprofessional responsible for deploying and managing yourorganization's business intelligence systems, this guide will helpyou make the most of PowerPivot. Professional Microsoft PowerPivot for Excel andSharePoint describes all aspects of PowerPivot and showsyou how to use each of its major features. By the time you arefinished with this book, you will be well on your way to becoming aPowerPivot expert.This book is for people who want to learn about PowerPivot fromend to end. You should have some rudimentary knowledge of databasesand data analysis. Familiarity with Microsoft Excel and MicrosoftSharePoint is helpful, since PowerPivot builds on those twoproducts.This book covers the first version of PowerPivot, which shipswith SQL Server 2008 R2 and enhances Microsoft Office 2010. Itprovides an overview of PowerPivot and a detailed look its twocomponents: PowerPivot for Excel and PowerPivot for SharePoint. Itexplains the technologies that make up these two components, andgives some insight into why these components were implemented theway they were. Through an extended example, it shows how to build aPowerPivot application from end to end.The companion Web site includes all the sample applications andreports discussed.
Computers & Technology >> Business Technology >> SharePointComputers & Technology >> Programming >> Microsoft Programming >> SQL ServerComputers & Technology >> Databases & Big Data >> Data Warehousing

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