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What is the difference between Data Warehousing, Business Intelligence and Data Mining.

May 14, 2011 2 comments

Often Data-Warehousing and Business-Intelligence are used interchangeably in day-to-day life. There is however a significant difference. Business-Intelligence drives Data-Warehousing requirements and consumes the end product that Data-Warehousing produces. And Data-Mining is an advanced level of Data-Warehousing and Business-Intelligence put together.

Data-Warehousing is the process of centralizing (at the least, the access of) all the data sources available in an organization/company. This centralization, of course, includes history-preservation, removal-of-ambiguities and optimization-for-fast-access amongst other things.  Data-Warehousing produces a Data-Warehouse; a centralized non-ambiguous and easily accessible historical set of all the data-sources.

Unlike commonly understood as an act of creating reports and dashboards, Business-Intelligence is in fact an act of identifying KPIs for various business verticals and their inter-dependence. Business-Intelligence is the guiding force behind the Data-Warehousing requirements. Business-Intelligence is also a process of discovering expected or unexpected actionable data-points from the Data-Warehouse that are of direct benefit to the business. Creation of reports and dashboards falls more under the scope of Data-Warehousing than Business-Intelligence.

Data-Mining begins where Data-Warehousing and Business-Intelligence ends. Data-Mining has not yet been classified into two separate segments like Data-Warehousing (for technical work) and Business-Intelligence (business related work). Data Mining uses the Data Warehouse in addition to preparing its own sets of sparse/dense wide and/or normalized data. Data-Mining may also use publically available data for benchmarking, comparing company data. Like Business-Intelligence, Data-Mining too discovers actionable data-points from the Data-Warehouse that are of direct benefit to the business,  but, in addition, it analyzes all the data using sophisticated mathematical/statistical/algorithmic techniques for making startling discoveries that are used more by the central strategic divisions in the company rather than the individual business units.