Data management plays several roles in an organization’s data environment, making essential functions easier and less time-intensive. These data management techniques include the following:

• Data preparation : Data preparation is used to clean and transform raw data into the right shape and format for analysis, including making corrections and combining data sets.
• Data pipelines : Data pipelines enable the automated transfer of data from one system to another.
• ETLs (Extract, Transform, Load) : ETLs (Extract, Transform, Load) are built to take the data from one system, transform it, and load it into the organization’s data warehouse.
• Data catalogs : Data catalogs help manage metadata to create a complete picture of the data, providing a summary of its changes, locations, and quality while also making the data easy to find.
• Data warehouses : Data warehouses are places to consolidate various data sources, contend with the many data types businesses store, and provide a clear route for data analysis.
• Data governance : Data governance defines standards, processes, and policies to maintain data security and integrity.
• Data architecture : Data architecture provides a formal approach for creating and managing data flow.
• Data security : Protects data from unauthorized access and corruption.
• Data modeling : Data modeling documents the flow of data through an application or organization.