Accounting Information Systems
Introduction
Data warehousing refers to a relative collection of data that has been designed and developed to
assist the management in making critical decisions. Data warehouses store enormous amount of
data that can provide a good view of all the business conditions at any particular moment.
Incorporating the external data mostly increases the value of the data warehouse. Many data
warehouses always focus on getting data from the internal operating systems. External data is the
data outside the company’s operating system. Data retrieved from the company’s spreadsheets
can be included in the SAS/ACCESS.( registered trademarks of SAS institute)
Find current examples of data warehousing software….why do companies create data
warehouses and what are some accounting uses of such warehouses?
Data warehousing software examples are like the IBM Banking Process and the service models,
DB2
For the windows family, UNIX and Linux, DB2 Advanced Workgroup Server Edition. Data
Warehouse or DW is a particular data base that is mostly used for management reporting and
data analysis. It’s the major and central repository of all data that’s created by the integration of
more disparate and reliable sources. Data Warehouses store all the information needed by
accompany which includes all the historical data as well as the current ones. Data warehousing
creates all the reports for the senior management team for instance quarterly comparative results
as well as the annual reports. (Inmon, 1992) OLAP accommodates complex, analytical and ado
2 Accounting
queries with very fat rapid response time. The OLAP dimensions can be added to the structure
for example stores and the stores department cashier also and his cash sales.(Inmon, 2005)
Find current examples of online analytical processing (OLAP)…why do companies use OLAP?
What is connection between OLAP and databases?
Online analytical processing, in computing, is a concept to answering the multi-dimensional and
analytical queries in a much faster and swifter way. Online analytical processing is also a major
part of the wider category of the business information intelligence, which includes the relational
databases, data observation and mining together with report writing. The major application of
the OLAP is mostly in the Business process and management, financial reporting, normal
company budgets and forecasts. Online analytical process evolved from the earlier online
transaction processing. OLAP provides the tools to analyze all the multidimensional data.
(Kimball, 1996) OLAP is composed of three major analytical,
i.e. roll up, or drill down, slicing and dishing. Online Analytical Processing (OLAP) is one of the
technologies that are applied in the organization. The OLAP databases are divided into cubes
which are designed to fit exactly where they have been designed to fit. For example, Excel
comes with the data source and customers software that’s needed to activate the databases with
the current SQL Server OLAP services. (Codd, Codd, and Salley, 1993).
The excel OLAP connects two other databases of OLAP databases. Once the data found on the
OLAP server is available on the network it can be located and retrieved easily. A data source
gives access to all the data in the OLAP data base or the offline cube file. OLAP is normally
characterized by low volumes of business transactions. The queries are also very complex. In
OLAP the databases are aggregated and stored in schemas. OLAP system is also a data
warehouse while the OLTP i.e. the online transactional processing is the operational system.
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References
Inmon, B. (1992). Building the Data Warehouse. Wiley.
Kimball, R. (1996). The Data Warehouse Toolkit. Wiley.
Codd E.F., Codd S.B., and Salley C.T. (1993).
“Providing OLAP (On-line Analytical Processing) to User-Analysts: An IT Mandate” . Codd &
Date, Inc. Retri
Inmon, W. (2005) Building the Data Warehouse: John Wiley and Sons,
