ITM535 MOD3 Discussion: Data Warehousing and Management
Describe how Data Warehouses can be used in Business Intelligence systems. How is data put into a Data Warehouse from Big Data Analytics?
Data Warehousing and Archive Management
Required Readings
Information Integration and Governance (2014). http://www-01(dot)ibm(dot)com/software/data/information-integration-governance/
Mailvaganam, Hari (2011). Data warehouse review: Introduction to project management. http://www(dot)dwreview(dot)com/Articles/Project_Management.html
Dyche, Jill (2011) The politics of data warehousing, http://www(dot)taborcommunications(dot)com/dsstar/00/0208/101300.html
Wherescape USA Inc (2015). Doing much more with much less: the case with data warehouse automation. Retrieved from http://www(dot)teradataemea(dot)com/universe/amsterdam/wp-content/uploads/2015/04/sc_Wherescape-3-10-2015-Data-Warehouse-Automation-Brochure.pdf
Optional Readings
Suppiah, Subra. Data Warehouse and Business Intelligence Glossary http://www(dot)kbase(dot)com/pdf/DWglossary.pdf
Baseline Magazine Resources http://www(dot)baselinemag(dot)com/category2/0,1568,655831,00.asp
Larry Greenfield (2006). Getting Started with Learning About Data Warehousing
Discussion Essay
Name
Institution
Discussion Essay
Data warehouse is subject-oriented, time-variant, integrated and non-volatile collection of data that enhances management’s decision making process. On the other hand, business intelligence systems are the applications, tools and infrastructure as well as the best practices that grant access to and analysis of information to optimize and improve decisions and performance. Various IT processing that is involved in warehouse data can be used in business intelligence to analyze those operations so as to optimize and improve them. For example, business transaction applications that run daily business operations could be applied in business intelligence in optimizing transactions and improving their flow. The data warehouse act as the site from which the business intelligence systems extract data for analysis and providing decisions (Baesens, 2014).
To optimize and improve business decisions, data warehousing emphasizes capturing or gathering of data from varied sources. Data captured from diverse sources is much useful for informative analysis and forecasting of the larger business environment. Data wareh...