Applied Microsoft Business Intelligence
Applied Microsoft Business Intelligence

Author: Patrick LeBlanc, Jessica M. Moss, Dejan Sarka & Dustin Ryan
Publisher: Wiley
Date: June 17, 2015
Pages: 432
ISBN: 978-1118961773
Print: 1118961773
Kindle: B00XCB148G
Aimed at: Business decision makers
Rating: 3.5
Reviewed by: Kay Ewbank

Microsoft's collection of business intelligence (BI) software is extensive and well integrated, but it's not that easy for the casual observer to work out what's available, which bit to use and how to use it. Does this book help?

Over the years Microsoft has acquired and developed some very impressive tools, and this book is intended to show how to make use of them to create your own enterprise BI solution. The book isn’t aimed at developers, but it might be useful if you’re trying to work out which tools do which bits in the Microsoft BI stable.  

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The first part of the book is an overview of the Microsoft BI toolset, introducing SQL Server Analysis Services, Reporting Services, SharePoint, Performance Point, Excel’s tools, and the development tools – SQL Server Data Tools, Management Studio, Dashboard Designer and Report Builder. There’s a short chapter on designing a BI architecture, and another looking at how to make sure your data architecture fits your organization. While these chapters were fine as overviews, you’d need a lot more information to get these aspects right.

Part II of the book takes the different tools in turn and goes into more detail on how to use them, starting with Excel’s Power Query. Space is taken in this chapter on where and how to download and install Power Query, and how to import data from databases, the web and files. The rest of the chapter introduces transforming data, and M programming. On the whole, I think more coverage of these topics would have been much more useful rather than wasting the space on screenshots of things such as the install wizard and the software license terms dialog.

Next comes a chapter on choosing the right BI semantic model. There’s a discussion of the different data sources you could use for the data layer, and an overview of where each fits in terms of departmental projects, organizational projects, or team projects.

Power Pivot is the topic covered next. This emphasis on the Excel add-ins in the Microsoft BI suite is perhaps understandable, but does give an impression that this is a book aimed at users looking for a simple solution. As with Power Query, a lot of space is devoted to enabling and the basics of importing data before you get on to more useful information such as how to design optimal Power Pivot models or optimizing models for reporting. 

 

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At this point the book becomes a bit more useful, starting with a chapter on using the tabular model in Analysis Services. This was one of the later additions to Analysis Services, and has become popular because of the way you can use it to create flexible and scalable models using it. Having introduced tabular models, the next chapter covers multidimensional models, which are a lot trickier to design and use. The chapter mostly works through the cube creation wizard and the business intelligence wizard, but this is justifiable because creating models is so hard to get right.

There’s a good chapter on discovering knowledge with data mining that starts from a very basic level but that gets to topics such as the way the data mining algorithms in SQL Server Analysis Services (SSAS) work, so you can work out which algorithm to choose and create your data mining model.

Part III is titled Business Intelligence for Reporting, and it opens with a chapter discussing the different BI visualization tools in the Microsoft range – SQL Server Reporting Services, Power View, and Power Map. The authors then look at each of these tools in turn, discussing what types of report and data you should use the tool for, and what the best practices of using them are. The authors then go on to look at PerformancePoint Services, and how it can be used to create dynamic dashboard reports that managers can use see an overall picture then drill down to get more details. This was one of the more useful chapters in that it went rather further than some of the others.

The final part of the book covers deploying and managing BI solutions, starting with a chapter on implementing a self-service delivery framework. The main material of this chapter was about how to improve and manage your data quality, data governance plans, and creating master data sets, introducing SQL Server Data Quality Services and Master Data Services and showing how they fit in. The book ends with a chapter on designing and implementing a deployment plan, and a final chapter on managing and maintaining the business intelligence environment.

This book provides a useful introductory roundup of the complex family of software Microsoft offers for business intelligence, but it doesn’t go very far into any of them, and I felt too much time was wasted on installation and walkthroughs of simple wizards. There was useful material in comparing why one product would be preferable to another in various circumstances, and so long as you’re only wanting to get an overall feel for the products and what they can do it is still a useful read.  

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Learning Computer Architecture with Raspberry Pi

Author: Eben Upton, Jeffrey Duntemann, Ralph Roberts, Tim Mamtora, and Ben Everard
Publisher: Wiley
Pages: 558
ISBN: 978-1119183938
Print:1119183936
Kindle:B01KW9E28Y
Audience: Those interested n the inner workings of hardware
Rating: 4
Reviewer: Harry Fairhead

Finding out how compute [ ... ]



Learn Python Quickly

Author:  John Rowland
Publisher: Amazon Digital Services
Pages:327 
Kindle:B00BU3LIOI
Audience: Complete beginners
Rating: 3
Reviewer: Alex Armstrong

Who would want to learn Python slowly? But there is a lot of Python to learn, so how quick is quick?


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Last Updated ( Monday, 27 July 2015 )
 
 

   
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