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Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence�Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.
- Sales Rank: #9156084 in Books
- Published on: 2010-12-07
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .64" w x 6.10" l, .87 pounds
- Binding: Paperback
- 268 pages
Most helpful customer reviews
6 of 6 people found the following review helpful.
A bit thin...
By Peter Koller
This is a collection of academic articles describing various aspects of business intelligence. Allthough the articles are interesting in themselves, the title of the book hints at a more hands-on approach than actually found in the text. Also the Accounting and Finance perspective is marginally represented, with no more than parts of two chapters devoted to the subject. I would say that about 60% of the book is an introduction to the world of business intelligence giving a birds eye view of subjects like ETL, OLAP and datawarehousing. 30% of the book is about more or less related subjects like the business reporting xml schema. Finally about 10% of the book actually handles accounting and finance. I was a bit disappointed.
0 of 0 people found the following review helpful.
Great Book!
By Business Intel Guy
I have scoured the internet in search of a concise discussion of accounting data warehouses. This book finally provides some clear guidance. Chapters 3 and 4, in particular, provide the best explanation yet of how accounting data warehouse requirements are different from sales data warehouses. Bravo to this book.
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