What is the process of extracting and filtering discrete data from a relational database called?

The process of extracting and filtering discrete data from a relational database is referred to as data mining. This involves utilizing various techniques to uncover patterns, relationships, or insights from large sets of data. In the context of a relational database, data mining allows analysts to perform operations such as querying, segmenting, and analyzing data to derive valuable information that can inform business decisions or clinical strategies.

Data mining encompasses a range of methods, including statistical analysis, machine learning, and artificial intelligence, which help in discovering meaningful correlations within the data. By applying these techniques, data analysts can transform raw data into actionable knowledge that supports various organizational goals.

In contrast, data warehousing pertains to the storage and consolidation of large volumes of data from different sources into a single repository for easier analysis and reporting. Data visualization focuses on representing data visually through graphs, charts, and dashboards to help users understand complex information more easily. Data governance involves the management of data availability, usability, integrity, and security within an organization, ensuring that data is properly handled and maintained.