Data Management: What It Is, Importance, And Challenges

What is data management?

Data management is the practice of collecting, organizing, protecting, and storing an organization’s data so it can be analyzed for business decisions. As organizations create and consume data at unprecedented rates, data management solutions become essential for making sense of the vast quantities of data. Today’s leading data management software ensures that reliable, up-to-date data is always used to drive decisions. The software helps with everything from data preparation to cataloging, search, and governance, allowing people to quickly find the information they need for analysis.

Types of Data Management

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 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 enable the automated transfer of data from one system to another.
• 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 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 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 defines standards, processes, and policies to maintain data security and integrity.
• Data architecture provides a formal approach for creating and managing data flow.
• Data security protects data from unauthorized access and corruption.
• Data modeling documents the flow of data through an application or organization.