Data mining Process : It generally involves analyzing data to find relations that were not previously discovered. In this case, the emphasis is on finding unusual records, detecting dependencies, and analyzing clusters. It also involves analyzing large datasets to determine trends and patterns in them.
Data Profiling Process : It generally involves analyzing that data's individual attributes. In this case, the emphasis is on providing useful information on data attributes such as data type, frequency, etc. Additionally, it also facilitates the discovery and evaluation of enterprise metadata.
| Data Mining |
Data Profiling |
| It involves analyzing a pre-built database to identify patterns. |
It involves analyses of raw data from existing datasets. |
| It also analyzes existing databases and large datasets to convert raw data into useful information. |
In this, statistical or informative summaries of the data are collected. |
| It usually involves finding hidden patterns and seeking out new, useful, and non-trivial data to generate useful information. |
It usually involves the evaluation of data sets to ensure consistency, uniqueness, and logic. |
| Data mining is incapable of identifying inaccurate or incorrect data values. |
In data profiling, erroneous data is identified during the initial stage of analysis. |
| Classification, regression, clustering, summarization, estimation, and description are some primary data mining tasks that are needed to be performed. |
This process involves using discoveries and analytical methods to gather statistics or summaries about the data. |
