Previously, I was in high-tech, now I'm in healthcare. In both instances, we used this solution to increase data literacy and business literacy. In short, we were building out business glossaries, coming to an agreement on term definitions, understanding what reports mean, what the metrics and calculations mean — essentially getting it all documented in an enterprise-facing view. That was the bulk of the focus in my prior company — along with some reference data. At my current company, we are focused heavily on bringing in data dictionaries, including schema tables and columns, and understanding what data is in which database. We also look at what data is flowing from database to database and how it's used in Tableau reports or in a business or archive.
Currently, we're on-premises, but we're planning on moving to the cloud later this year.
Over the last 12 months, we've had 643 unique new users. Most of our users tend to be what I would call "data geeks". They are the ones that understand the value of and/or the aspect of leadership to catalog their metadata for their data dictionaries, etc. The business users have not had as much adoption at my current company because that's not the particular strategy at this time. At my prior company, that was the singular strategy — to increase business literacy.
In regard to my previous company, for eight years, our primary customers were business users, not technical users. They just wanted to come in and say, "What does it mean? Who do I talk to if I have questions? Where do I go for more information? How does this relate to that, and how do those things affect me in my business world?" That was a fantastic use case at my prior company. In my current company, we're utilizing the tool specifically to support our data management strategy. Our technology risk office is very much supporting us in the effort to do the cataloging of all of the metadata for all of the systems that we're utilizing, cross-functionally.
Maintenance must be defined. As with any software product that exists, there are regular maintenance upgrades that occur that the company pushes out. If you're on-prem, you can choose to do it sooner versus later. In the Cloud, they push it to you unless you state that you wish to wait. From a maintenance perspective, I have talked to other customers who are in a cloud environment. They say that the maintenance has basically dropped to nil. For on-prem customers, it does require a little more maintenance because obviously, you've got to make sure that the servers are up and running, etc. In my prior role at my previous company, I was responsible for the business IT side of it, which meant I kind of managed the platform. I just didn't manage the server.
I took care of the customers, etc. I'm not even a technical person at all, but still, it was not difficult for me. From a maintenance perspective, I don't feel that it is difficult.
If you have custom integrations that have been created, then it will require a little bit more maintenance because those integrations need to be monitored. Some customers require a lot of integration, and some customers don't. It really depends upon the use case. Custom integration is really where it gets more challenging. Depending on whether it's a one-way integration or a two-way data feed, it can get pretty complex. Two-way data feeds are always custom. But that's something that will be on the customer anyway, not Collibra.
We've only just relaunched this solution within the last 15 months. Currently, we only have about 240,000 assets in the tool, but we have a roadmap and plan to onboard a number of our customers. We'll probably double or triple our users over the next 12 months.
This solution has brought our very diverse cross-functional business teams to one enterprise-facing view, where they can see business glossaries that have been compiled by other teams. From here, they can leverage and understand what reports have been created. If the report exists already, why recreate it?
Our data management strategy is to start cataloging our data dictionaries and our business glossaries to ensure that we have a common platform across the company. This is helpful when a database is being retired or being converted over to another one. A lot of work goes into documenting what that data attribute means, or what that field name means in regard to a particular report, or in a particular database.
