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Data Warehousing and Data Mining in Business Applications


Affiliations
1 CSE Deptt., GZS-PTU Campus, Bathinda, India
 

Information technology is now required in all aspect of our lives that helps in business and enterprise for the usage of applications like decision support system, query and reporting online analytical processing, predictive analysis and business performance management. This paper focuses on the significance and role of Data Warehousing and Data Mining technology in business. Data Warehouse is a central repository of relational database designed for query and analysis. Business organization uses this technique to consolidate data from different varying sources. The latest technique used for analyzing these warehouses is known as Data Mining. In Data Mining data sets will be explored to yield hidden and unknown predictions that can be used in future for the efficient decision making. In global data now companies use techniques of Data Mining that includes pattern recognition, mathematical and statistical techniques for searching Data Warehouses and to help the analyst in recognizing significant trend, facts relationships and anomalies.

Keywords

Data Warehousing, Data Mining, OLAP, OLTP.
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  • Data Warehousing and Data Mining in Business Applications

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Authors

Eesha Goel
CSE Deptt., GZS-PTU Campus, Bathinda, India

Abstract


Information technology is now required in all aspect of our lives that helps in business and enterprise for the usage of applications like decision support system, query and reporting online analytical processing, predictive analysis and business performance management. This paper focuses on the significance and role of Data Warehousing and Data Mining technology in business. Data Warehouse is a central repository of relational database designed for query and analysis. Business organization uses this technique to consolidate data from different varying sources. The latest technique used for analyzing these warehouses is known as Data Mining. In Data Mining data sets will be explored to yield hidden and unknown predictions that can be used in future for the efficient decision making. In global data now companies use techniques of Data Mining that includes pattern recognition, mathematical and statistical techniques for searching Data Warehouses and to help the analyst in recognizing significant trend, facts relationships and anomalies.

Keywords


Data Warehousing, Data Mining, OLAP, OLTP.