W1 Asig Datawarehouse - Essay Example

Data Warehouse: Business Intelligence al Affiliation Data Warehouse: Business Intelligence First and foremost, the conceptof business intelligence is applied to data warehousing and analytics through understanding of its theoretical framework. As defined, business intelligence (BI) is “the systems and technologies for gathering, cleansing, consolidating,and storing corporate data. Next, business intelligence relates to the tools, techniques, andapplications for analyzing the stored data” (Ponniah, 2010, p. 18). Concurrently, within an organizational setting, BI is described as enabling taking “data as the raw material, collects it, refines it, and processes it into several information products” (Ponniah, 2010, p. 18). As such, in one’s corporate setting where IT is deemed a crucial source of information and response to inquiries needed by other departments, especially by the marketing department, the apparently slow response could be attributed to the sources of information that needs to be tapped before it could be disseminated to end users.

The model below clearly depicts the flow of information from operational systems to end users:Figure 1: Business Intelligence: Data Warehousing and Analytical Environments Source: (Ponniah, 2010, p. 19) From the conceptual framework, it could be deduced that the operational systems undergo a series of processes on the information or data upon solicitation: extraction, integration, cleansing, and transformation. This information is then stored in the organization’s data warehouse to serve varied needs and demands of the users.

The cause of delays in soliciting data from the external environment could be diverse: from frequent changes in factors affecting the external environment to the need to update currently available information. As emphasized, “reports generated in high data volume environments normally take a long time to run. To speed up report generation, many systems use tools that employ a summarization technique to reduce the amount of records by aggregating records together with common characteristics.

Problem with this technique includes inherent inflexibility and inability to cope with the constantly changing information needs of manufacturing” (MAIA Intelligence, 2009, p. 4). Overall, the information gathered by the IT department needs to be processed and transformed in the most accurate manner before being transformed and stored to the organization’s data warehouse. As such, the delay should be understandable given the volume of information from the external environment that needs to be summarized and integrated according to the users’ needs.

Concurrently, experts in BI has asserted that “business leaders want to obtain real metrics and near-real-time, linked directly to the business processes, system data and insights from people” (Mohta, 2010, p. 24). Therefore, depending on the kind and type of information being required by personnel from the marketing department, IT personnel could only respond according to the availability of the most accurate information which could be solicited given the time frame at hand.ReferencesMAIA Intelligence. (2009). Business Intelligence in Manufacturing.

Retrieved October 31, 2014, from slideshare.net: http://www.slideshare.net/businessintelligence/business-intelligence-bi-for-manufacturing-a-white-paperMohta, S. (2010, April). Drive automotive operations in the fast lane with business intelligence. Retrieved October 31, 2014, from maia-intelligence.com: http://www.maia-intelligence.com/pdf/BI-for-automotive-Auto-Monitor.pdfPonniah, P. (2010). Data Warehousing Fundamentals for it Professionals. John Wiley & Sons, Inc.