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Difference between Data Warehousing and Data Mining
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Data Warehousing
A data warehouse is built to support management functions whereas data mining is used to extract useful information and patterns from data. Data warehousing is the process of compiling information into a data warehouse.
Data warehouse consolidates data from many sources while ensuring data quality, consistency and accuracy. Data warehouse improves system performance by separating analytics processing from transnational databases. Data flows into a data warehouse from the various databases. ( Codeithub )
A data warehouse works by organizing data into a schema which describes the layout and type of data. Query tools analyze the data tables using schema.
Data Mining:
Data mining refers to the analysis of data. It is the computer-supported process of analyzing huge sets of data that have either been compiled by computer systems or have been downloaded into the computer.( social media website github )
Data warehousing and data mining are two popular and essential techniques to store and analyze data.
Difference between Data Warehousing and Data Mining
Data Warehousing
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A data warehouse is a database system which is designed for analytical analysis instead of transactional work. |
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Data is stored periodically. |
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Data warehousing is the process of extracting and storing data to allow easier reporting. |
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Data warehousing is solely carried out by engineers. Data warehousing is the process of pooling all relevant data together. Data warehousing is done for large business projects where the other companies can integrate their data with such platforms. Thus, it needs to have high maintenance and proper execution of warehousing techniques. |
Data Mining
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Data mining is the process of analyzing data patterns. |
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Data is analyzed regularly. |
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Data mining is the use of pattern recognition logic to identify patterns |
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Data mining is carried by business users with the help of engineers. |
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Data mining is considered as a process of extracting data from large data sets. |
The data mined by the company can misplace with the groups of people if it is not done correctly. Hence it requires a detailed approach and systematic effort. ( Codeithub )
Conclusion
Both data mining and data warehousing are crucial processes to prevent data fraud at organizational levels and improve organization statistics and ranking. Data warehouses store information records and data mining techniques contribute towards extracting relevant information and data in accordance with requirements. Both processes work in tandem to improve and facilitate the management of any organization.
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