Online Datawarehouse



Youness (2000) explained that a datawarehouse integrates data from several sources, and consolidates this data in a common database. The datawarehouse organizes and stores the data needed for informative analytical processing over a long historical time perspective. The data is thus stored as snapshots of the corporate business in time. Datawarehouse stores data collected from the corporate OLTP applications, and also may store the data generated by the OLAP reports to facilitate quick retrieval when needed.  

Reed (n.d.) explained that the datawarehousing is defined as the technology and the methodology that allow the construction, and the usage of data within an organization for the decision making. Bill Inmon in 1990 defined the datawarehouse as an integrated well oriented of non-volatile collection of data that is used in support of the management’s decision making process.

Browning and Mundy (2001) explained that datawarehouse is subject oriented because the data gathered gives information about specific subject instead of the company’s ongoing operations (Operational database). The data within the datawarehouse is considered integrated because it’s a collection of data from different resources, and identified under particular time period. One of the main job that datawarehouse can provide is to support business decisions  by organizing data, collecting and consolidating data for reporting and analysis with tools such as online analytical processing (OLAP) and data mining. Despite the fact it is built based on the relational database concept of technology, the design of the datawarehouse database differs from the online transaction database (OLTP) or the operational database. The datawarehouse architecture must be designed to provide the following requirements:


  • Able to function without interfering with OLTP systems.
  • Represents a consistent data in a central repository.
  • Be able to answer the corporate complex queries in a timely fashion.
  • Be able to provide powerful analytical tools such as data mining and OLAP.
  • Be able to consolidate variety of data from multiple sources while maintain consistency.
  • Be able to perform a subject oriented for the query processes such as sales, inventory, or finance.

Why we need online datawarehouse

In the e-business environment the main challenge is to find the right technology that can provide the e-business with efficient operations and also provide the right solution to understand its market. The datawarehouse can help e-business to create the total picture of the market behavior that goes beyond actual customers. By understanding customers through the datawarehouse analytical tool, e-business can achieve market growth by converting the non-customers to business customers (Sweiger and Langston, 2002).

One of the techniques that can be used by datawarehouse is the web server log file analysis tools, such tools can provide different statistics that can be a source of data to the datawarehouse system that can help e-business to grow. Such tool can provide recording site hit statistics, site exit pages, site entry and other statistics. Such data can provide overall trends over time which will identify certain audience and interests. With such data accumulated in the log file analysis tools can be used as part of the input data for the datawarehouse which can provide different indication of the customer behaviors (Sweiger and Langston, 2002).

Web-based datawarehouse

With the web-based information; the up to-date analysis and decision making plays an important role in the current global market and society. With such new era the efficient integration of various web data is needed to provide the vital resources to the e-business (Rahayu, 2008).

Web datawarehousing is a growing area related to the e-business and most of the web-based applications that can address the need of an efficient web data summary to support decision making and ensure the web data analysis quality. It’s a common practice these days with the growing trend of the online business to represent the information structure in an XML format that is used for business processes and data exchange between businesses (Rahayu, 2008).

Rob (1999) explained that web datawarehouse has the same architecture complexity as any typical corporate datawarehouse.  Having the web datawarehousing environment, the organization can take advantage of the web technology that can leverage lower cost, flexibility and the availability of the web to deploy such applications around the world without the need for expensive dedicate internal managed networks of any organization. Also, end-user can gain access to such information locally through the internal corporate access network or via public web server. With many different configurations to choose from, to manage the speed and represent that data based online; some challenges and special skills are required. Some of these challenges are:


  • The performance of any system depends on the performance of each component such as the web server, the database, and the internet connections.
  • The workload that each component will place on the system.
  • The capacity of such system that can be measured by what rate transactions are generated, how often data gets moved or handled for each transaction, and how many transactions are generated or handled within a given time frame.  

With measuring the transactions per hour will give an indication of how much workload a component of the system generate and how other components will be able to deal with that workload (Rob,1999).


Datawarehouse serves in any business as a central repository for information data that is based on a relational database that can help business understand market behavior; answering quickly questions via different queries, and help businesses to make the right decisions. The source of data that is fed to the datawarehouse is the corporate operational applications databases. As the data stored in the warehouse, it is transformed into an integrated cleaned structured and formatted data. Since the datawarehouse contains a historical data it must be capable of managing and holding large volumes of data, and also to maintain different data structure of same database (Berson and Smith, 1997).

With the web datawarehousing technology implemented in many businesses structure, such system will allow business users to analyze how well their business are running, and how to run it better. Datawarehouse is the diagnostic system of the business lifecycle. With datawarehouse contributions on the web, it can provide business data online world wide with low cost since the web technology is used instead of the corporate network. Also, the web datawarehousing makes it easy for business users to get what they need quickly, and effectively to answer the questions needed for business decisions making.


Berson, A. & Smith S. (1997) Components of a Data Warehouse [Online]. Available from: (Accessed: 6 March 2010).

Browning, D. & Mundy J. (2001) Data Warehouse Design Considerations [Online]. Available from: (Accessed: 6 March 2010).

Rahayu J. (2008) The new era of web data warehousing: XML warehousing issues and challenges [Online]. Available from: (Accessed: 6 March 2010).

Reed, M. (n.d.) A Definition of Data Warehousing [Online]. Available from: (Accessed: 6 March 2010).

Rob, M. (1999) Web warehousing and Knowledge Management [Online]. Available from: (Accessed: 6 March 2010).

Sweiger, M. &Langston J. (2002) Clickstream Data Warehousing [Online]. Available from: (Accessed: 6 March 2010).

Youness Sakhr (2000) Professional Data Warehousing with SQL Server 7.0 and OLAP Services. 2nd ed. Brimingham:Wrox Press.














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