Metadata refers to the detailed information about the data system and its contents. It helps to define the type of data or information that will be sorted.

In the context of data analytics, metadata refers to descriptive information about the characteristics of data. It provides context and structure to the data, helping users understand its content, quality, and meaning. Metadata typically includes details such as:

Data Source: Information about where the data originates from, including its source system, database, or application.
Data Structure: Details about the format and organization of the data, such as data types, field names, and relationships between different data elements.
Data Quality: Metrics and indicators related to the quality of the data, such as completeness, accuracy, consistency, and timeliness.
Data Usage: Information about how the data is intended to be used, including any restrictions or permissions associated with accessing or modifying the data.
Data Lineage: Traceability of data from its source through various transformations and analyses, documenting its journey within an organization.
Data Governance: Policies, standards, and procedures governing the management and use of data, including security and privacy considerations.

Overall, metadata plays a crucial role in data management, facilitating data discovery, integration, analysis, and governance processes. It helps users locate relevant data, assess its reliability, and make informed decisions based on the insights derived from the data.