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Data mining and data profiling

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What are the major differences between data mining and data profiling.

  1. Data Mining

    Data mining is used to extract data from large data I mean from Big Data. Data mining is done to discover some knowledge in databases. The need of data mining is to identify interesting patterns and establish relationships to solve problems through data analysis.

    Data Profiling

    Data profiling is the process of examining source data. Data profiling is usually performed using a statistical analysis which helps to recognize the use and data quality of metadata. This method is widely used in enterprise data warehousing.

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  2. Data profiling is being done at different stages of data warehouse developing stages. The purpose of data profiling is to identify the wrong data at the initial stage of data so that it can be corrected at the right time. On the other hand, Data mining is the process of identifying patterns in the pre-built database. It is the process of evaluating the existing database and turning raw data into useful information. Data Mining involves evaluating the large blocks of datasets to draw patterns and trends in the database. We can break the data mining process into five steps gathering the data and loading it into the database.

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