Difference Between Data and Metadata
Many individuals are perplexed by the terms Data and Metadata. Though both are data types, they serve different purposes and have different requirements.
Data might simply be a piece of information, a series of measurements or observations, a tale, or a description of anything. Metadata specify important information about the data that aids in determining the type and characteristics of the data.
Data is composed of information that includes observations, measurements, facts, and descriptions of various objects. It enables you to identify patterns and trends in all of an enterprise's data assets.
Metadata, sometimes known as "data on data," refers to detailed facts about this data. It gives detailed information on a single piece of data, such as file type, format, origin, date, and so forth.
Why is Metadata important for Data Management?
Metadata is formed when data is created (its origin, format, type, etc.). This information, however, is insufficient to adequately manage data in this developing digital world; data managers must devote effort in ensuring that this business asset is correctly identified, tagged, stored, and preserved in a taxonomy that is consistent with all of the other assets in the firm. This is referred to as "metadata management."
Better metadata management results in higher data value. This information enables organizations to improve data quality and discovery, allowing data teams to better understand their data. Without metadata, enterprises are left with datasets devoid of context, and data devoid of context has little value.
This is why having a proper metadata management solution is critical for enterprises dealing with data. By implementing a metadata management platform, data users are able to discover, understand, and trust their enterprise’s data assets.
