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Data Warehousing and Data Mining

It was recognized that information is at the heart of business operations and that decisionmakers could make use of the data stored to gain valuable insight into the business. Database Management Systems gave access to the data stored but this was only a small part of what could be gained from the data. Traditional on-line transaction processing systems, OLTPs, are good at putting data into databases quickly, safely and efficiently but are not good at delivering meaningful analysis in return.

  • Analyzing data can provide further knowledge about a business by going beyond the data explicitly stored to derive knowledge about the business.
  • Data Mining, also called as data archeology, data dredging, data harvesting, is the process of extracting hidden knowledge from large volumes of raw data and using it to make crucial business decisions.
  • This is where Data Mining or Knowledge Discovery in Databases (KDD) has obvious benefits for any enterprise.

The term data mining has been stretched beyond its limits to apply to any form of data analysis. Some of the numerous definitions of Data Mining, or Knowledge Discovery in Databases are: Extraction of interesting information or patterns from data in large databases is known as data mining.

Data warehousing is a collection of decision support technologies, aimed at enabling the knowledge worker (executive, manager, analyst) to make better and faster decisions. Data mining potential can be enhanced if the appropriate data has been collected and stored in a data warehouse. A data warehouse is a relational database management system (RDBMS) designed specifically to meet the needs of transaction processing systems. It can be loosely defined as any centralized data repository
which can be queried for business benefit but this will be more clearly defined later. Data warehousing is a new powerful technique making it possible to extract archived operational data and overcome inconsistencies between different legacy data formats. As well as integrating data throughout an enterprise, regardless of location, format, or communication requirements it is possible to incorporate additional or expert information.

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