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I have been working in the data domain for quite some time now, and over the years, I have utilized and analyzed various applications for data analytics, governance, and cataloging. One dire need of every data-driven organization these days is to find the data that they are looking for as quickly as possible, to make quicker business decisions. However, with the overwhelming growth of the data, the data sources are proliferating as well. As a result, it is becoming much more laborious and more time consuming to find the appropriate data and utilizing it.

To give you an example, a medium-sized bank has 1000’s of source systems where they store their data. This data is eventually stored in huge data lakes, and thus become a part of Big data. To manage and make sense of big data manually takes months and sometimes years of effort. Not just that, most of the times, this data is stored in silos, which makes it even more challenging for the business users to access other LOB’s data. The users always have to depend on the data specialists to find them the data. As a consequence, the analysts spend most of their time, looking for the right data, instead of analyzing it. Therefore, to create even a generic report takes months of work and a lot of resources. In order to access data across the organization, one needs to have a catalog of information assets, so that the analysts know where to look for the data. In most organizations, this process of cataloging is still being done manually.

There are, however, a few self-powered cataloging tools, which make the process of finding data across multiple domains and multiple source systems much more relaxed. Waterline is one of those tools. It is an AI, and Machine learning powered Data catalog that finds data across domains and multiple source systems by using the method of tagging and fingerprinting. Using this tool, business users himself can make those reports in a matter of a day or two. They don’t have to depend on data specialists and analysts to look for the data for them. Being a machine learning tool, waterline learns from your previous searches and understands your needs, as your phone learns about you. What makes Waterline standout is the way the UI of the catalog has been designed. The users can look for their data as if they were shopping online or browsing at a grocery store. They can see what data is coming from which source, and how it is stored and in what format. They don’t have to query the data but do a simple search like one would do on an online store.

I would love to talk more about it, find out how we can help you set-up your Data Governance practice. Please don’t hesitate to reach out to me at diksha.chawla@inceptds.com.

Diksha Chawla
Data Governance Lead @ Incept

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