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The Accounting Centric Data WarehouseTM

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Abstract

At the heart of every organization, regardless of location or industry, is the accounting function. The accounting function is responsible for gathering, recording, and reporting on all of the financial transactions consummated by the enterprise. Using sophisticated transaction applications, accountants aggregate financial activity from disparate functions of the business and record a summary of the transactions in the general ledger (GL). Within the GL, data is organized in the chart of accounts, which represents the physical organization of the business. Business units, departments, products, and accounts are examples of chart of account segments. Accounting then produces the financial statements (i.e., balance sheet and income statement) from the data in the GL. The financial statements are distributed to internal and external stakeholders to evaluate the performance of the enterprise.

This method of capturing and organizing data works very well; however when it comes to reporting and analysis, limitations exist. Transaction systems are not designed to support dynamic analysis. Complicated data models make querying the database an arduous task. In addition, reporting from the GL is limited to the intelligence captured in the chart of accounts. Therefore, to improve financial reporting capabilities, a different approach is used. This approach is an Accounting Centric Data Warehouse TM (ACDW). To build an ACDW, the data in the GL is extracted and joined in a separate repository with supporting data captured in the operational subsidiary ledgers (sub-ledgers). The sub-ledgers are the applications used to capture the operational transactions of the business. Sales orders, loan servicing, accounts payable, accounts receivable, and inventory are all examples of sub-ledgers. By creating a platform that brings the GL and sub-ledger data together, a deeper level of financial analysis is possible. The ACDW contains summary level balances from the GL down to the supporting transaction detail from the sub-ledgers. With an ACDW, top down or bottom up analysis is possible. Over time sub-ledgers can be incrementally integrated into the ACDW to create a single enterprise decision support platform.

Keywords

Data Warehouse Business Unit Disparate Function Financial Transaction Journal Entry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  1. 1.Claritee Group, LLCUSA

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