How to Provide Your Data Scientists with Easy Metadata Access

Analytics | Co-creation | Published 11. Jan. 17

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One of Central Europe's biggest banks (+7000 FTE) wanted to make it easier for their data scientists to access their metadata. Semanta was tasked to realize this.

When No One Understands the Data Modelling Tools 

The bank’s business department has about 200 people relying on data for decision-making. There’s no shortage of data, in fact there’s an overflow, but the problem is they’re inaccessible to the business users who are mainly data scientists. It’s not that it’s not within reach, but none of the data scientists know how to use the available data modelling tools. A small specialized group does and the data scientists have to rely on the group for access.

The whole situation is not only inefficient, it’s also very expensive. 

Enter Semanta

The bank was looking for a solution and discovered Semanta, which is a cataloguing/metadata management tool that allows for automatic data registration and connection to the company’s modelling tools and databases. It also makes a copy of the metadata and enables it to be accessible to users through an intuitive web interface. IntoDQ, experts in data quality and data governance, represents the Semanta solution in the Benelux area.

Efficiency and Self-Sufficiency Achieved

Through the solution, hundreds of thousands of bank records were made available to the data scientists — overnight — without having to send a request. 

Thanks to the easy-to-use intuitive web interface, which allows the records to be annotated, commented and the data enriched and documented real-time, the bank has been able to open its data models to all its employees. But the best part is that it can be done overnight, which is also just the amount of time needed to set up the connectors and copy the metadata.

All in all, the solution allowed the bank’s business users to work more efficiently and quickly — freeing its team of analysts to focus on other challenges.

Other benefits include:

  • Enriched documentation of data (even Big Data).
  • A single place place where employees can find what they need.
  • Elimination of time and extra money spent on complex modelling tools.
  • Usage of metadata catalog extended to other initiatives (for new applications and new user groups).

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