“Data is content, and metadata is context. Metadata can be much more revealing than data, especially when collected in the aggregate.”
— Bruce Schneier, Data and Goliath
Definitions of Data and Metadata
For the majority of people, the concepts of Metadata and Data are unclear. Even though both are a form of data, their uses and specifications are completely different.
Data is a collection of information such as observations, measurements, facts, and descriptions of certain things. It gives you the ability to discover patterns and trends in all of an enterprise’s data assets.
On the other hand, Metadata, often defined as “data on data”, refers to specific details on these data. It provides granular information on one specific data such as file type, format, origin, date, etc.
Key differences between data and metadata
The main difference between Data and Metadata is that data is simply the content that can provide a description, measurement, or even a report on anything relative to an enterprise’s data assets. On the other hand, metadata describes the relevant information on said data, giving them more context for data users.
Some data is informative and some may not be; such as “raw” data (numbers, or non-informative characters). However, metadata is always informative as it is a reference to other data.
Finally, data can or cannot be processed, as raw data is always considered unprocessed data. The difference with metadata is that metadata is always considered to be processed information.
Why is metadata important for Data Management?
When data is created, so is metadata (its origin, format, type, etc.). However, this type of information is not enough to properly manage data in this expanding digital era; data managers must invest time in making sure this business asset is properly named, tagged, stored, and archived in a taxonomy that is consistent with all of the other assets in the enterprise. This is what we call, “metadata management.”
With better metadata management comes better data value. This metadata allows for enterprises to assure greater Data quality and discovery, allowing data teams to better understand their data. Without metadata, enterprise find themselves with datasets without context, and data without 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 in their enterprise’s data assets.
Are you looking for a metadata management solution?