With the emergence of Big Data, enterprises found themselves with a colossal amount of data. In order to understand and analyse their data, as well as meet the various regulatory requirements, it is vital for organizations to document their data assets. However, documenting and giving context to thousands of datasets is a very difficult, even impossible, task to do by hand.

Or, you can use Data Fingerprinting!

What is Data Fingerprinting?

In the data domain, a fingerprint represents a “signature”, or fingerprint, of a data column. The goal here is to give context to these columns.

Via this technology, a Data Fingerprint can automatically detect similar datasets in your databases and can document them more easily, making data steward’s tasks less fastidious and more efficient. For example, supervised by the data steward, data fingerprinting technologies allow us to understand that a column of data with the information “France”, “United States”, and “Australia” represents “Countries”.

Data Fingerprinting at Zeenea

In Zeenea’s case, our metadata management platform’s objective is to give meaning and context to your catalogued datasets in the most automatic way as possible. With our Machine Learning technologies, Zeenea identifies dataset schema columns, analyses them and gives them their own “signature”. In this way, if any of these fingerprints are similar, our Data Catalog will make suggestions as to whether the Data Steward should give the same information relative to another.

This technology also gives a means for DPOs to, among others, underline and point out personal or sensitive information that the organization possesses in its databases.

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