Business Intelligence Techniques: A Perspective from Accounting and Finance

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Murugan Anandarajan, Asokan Anandarajan, Cadambi A. Srinivasan
Springer Science & Business Media, Nov 2, 2012 - Business & Economics - 268 pages
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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 these 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 of their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.

 

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Contents

Preface
1
Importance of Data in DecisionMaking
21
Populating the Accounting Data Warehouse
40
The Accounting Centric Data Warehouse
55
XBRL A New Tool For Electronic Financial Reporting
73
Online Analytical Processing in Accounting
93
Bankruptcy Prediction Using Neural Networks
117
Visualization of Patterns in Accounting Data with Selforganizing
133
Alignment of AIS with Business Intelligence Requirements
167
A Methodology for Developing Business Intelligence Systems
181
An OO Approach to Designing Business Intelligence Systems
196
A Balanced Scorecard Approach
213
A Stakeholder Model of Business Intelligence
227
References
243
Index
263
Copyright

Visual Representations of Accounting Information
148

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