Data warehouse, data mart and business intelligence - Essay Example

DATA WAREHOUSE, DATA MART AND BUSINESS INTELLIGENCE Data warehouse, Data mart and Business Intelligence Affiliation Business intelligence offers a wide variety of tools and techniques for collecting, storing, processing, and distributing huge volumes of data and information to improve business decision making capabilities. However, business intelligence’s design is usually composed of a data warehouse that combines data from a variety of sources such as corporate databases or information systems and serves a range of front-end reporting, querying and analytic tools (Dayal, Castellanos, Simitsis, & Wilkinson, 2009).

In addition, the data warehouse is a database of unique data structure that allows comparatively rapid and trouble-free performance of big and complex queries over large amounts of data (Business Intelligence Secrets, 2012). Additionally, the data warehouse is built to support the business intelligence tasks and decision support systems of an organization. However, the data warehouse is developed on the basis of relational database that supports queries and reporting instead of traditional business transaction processing.

Moreover, it typically holds historical data resulting from transaction data; as well it can gather data from other corporate sources. Also, it divides bossiness analysis workload from corporate operations workload and allows a business to merge data from numerous sources (Oracle Corporation, 2002; Einbinder, Scully, Pates, Schubart, & Reynolds, 2001).There is another concept related to business intelligence known as data mart, it is a business decision support structure that integrates data from different sources and focuses on major processes or tasks of the business.

In addition, the data marts encompass exact business related processes and principles like that forecasting sales, determining performance and influence of marketing promotions, assessing the influence of new product launching on business income or calculating and forecasting the working of a new business division or department. In fact, data marts are strictly business related software systems. Though, data marts can capture large amounts of data, even hundreds of gigabytes, but it cannot be larger than the data warehouse, which is also used by similar businesses.

On the other hand, data marts are more aligned with specific company motives, system requirements and planning and analysis are performed in an effective manner and as a result implementation, design, installation and testing are less expensive as compared to data warehouses (Demarest, 1993; Firestone, 1997).Moreover, the majority of business organizations implement data marts for the following reasons:Its price is less It does not necessitate digging into business level financial plansThere are fewer chances of interdepartmental clashesIn addition, they can be developed rapidly and they are able to rapidly create models of success as well as corporate populations that will appear positively on data mart systems.

In fact, they carry out exact processes for a department or division that are part of that unit’s normally associated with business or managerial roles and responsibilities, political justification of a business data mart is comparatively clear (Demarest, 1993; Firestone, 1997). The process of creating data marts is known as data marting that has a lot benefits over data warehousing. For instance, the data mart focuses on data legibility. In this scenario, an organization stores and processes only the necessary data, in a form that integrates shared reorganization of the corporation.

In addition, data mart makes effective use of LAN supported technology such as client-server that is combined with the knowledge workers toolset. Moreover, a data-mart offers a standardized population of knowledge staff with comparable business models, organizational roles and responsibilities (Chaudhuri, Dayal, & Narasayya, 2011; Demarest, 1993). However, these both tools (data marts and warehouses) are used to support the business intelligence tasks of organizations.ReferencesBusiness Intelligence Secrets. (2012). What is Data Warehouse?

Retrieved March 08, 2012, from http://www.business-intelligence-secrets.com/bi-questions-and-answers/what-is-data-warehouse/Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Communications of the ACM, Volume 54 Issue8, pp. 88-98.Dayal, U., Castellanos, M., Simitsis, A., & Wilkinson, K. (2009). Data integration flows for business intelligence. Extending Database Technology; Vol. 360, Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology (pp. 1-11). Saint Petersburg, Russia: ACM New York, USA .

Demarest, M. (1993, November). Building The Data Mart. Retrieved March 08, 2012, from http://www.noumenal.com/marc/marts.htmlEinbinder, J. S., Scully, K. W., Pates, R. D., Schubart, J. R., & Reynolds, R. E. (2001). Case Study: A Data Warehouse for an Academic Medical Center. Journal Of Healthcare Information Management, Volume 15 Issue 2, pp. 165-175.Firestone, J. M. (1997, March 27). Data Warehouses and Data Marts: A Dynamic View. Retrieved March 10, 2012, from http://www.dkms.com/papers/dwdmdv.

pdfOracle Corporation. (2002). Data Warehousing Concepts. Retrieved March 10, 2012, from http://docs.oracle.com/cd/B10501_01/server.920/a96520/concept.htm