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Data mapping as a service, a modern form of data discovery

The CEO of ActiveNav provides insight into how data mapping fits into the data management landscape as the vendor launches a new data mapping-as-a-service platform.

Data resides in many different places and figuring out how to navigate and identify it is no small challenge.

Among the many vendors that offer technology to help organizations with data management and discovery has been Active Navigation, based in Washington, D.C., and founded in 2008. Over the last dozen years, the data landscape has changed significantly, with organizations using more data, from more sources. The cloud and software as a service (SaaS) models have also grown in importance, as a location from which data is generated, as well as an approach for delivering application services.

On Sept. 1, the vendor made public the next phase of its evolution, rebranding itself as ActiveNav. Alongside the renaming, the vendor launched its new Active-Inventory service, a data mapping as a service (DMaaS) system for data discovery. DMaaS enables organization to identify and organize unstructured data and can help business users more fully utilize data assets.

In this Q&A, Peter Baumann, co-founder and CEO, discusses the evolution of ActiveNav and what data mapping is all about.

What was the founding vision for ActiveNav and how has it changed over the past dozen years?

Peter Baumann: We founded the business based on our ability to do unstructured data discovery with no prior knowledge. We could very quickly shine a light on data and help customers navigate through it. We built tool sets and workflows that would allow you to discover and categorize data, and the journey we've been on over the last 10 years or so has been about perfecting that.

ActiveNav CEO and co-founder Peter BaumannPeter Baumann

In the early days, Gartner had given our particular capability the label of file analysis. It's not the most exciting label, but it kind of does a good job of describing what it is we do, which is look at the large amounts of metadata attributes from data and try to pull some meaning from them.

So, the journey we've been on has been one of unstructured data discovery. We've largely done all of it through an on-premises environment approach. Over the last three or four years, a large amount of business has become geared toward the privacy governance requirements.

How has data mapping and discovery changed over the years?

Baumann: If you look at it from the way the customer tends to operate, the first thing they want to do is find out what they've got. So, effectively, it's a discovery exercise, for a specific project, like a litigation matter.

What we found over time is that organization see the value in doing data mapping on an ongoing basis. It's no longer just a one-time exercise. Organizations realize they need to keep data in a good state on an ongoing basis. And so, our product set has kind of followed that market motion.

Organizations really struggle with unstructured data. It's still one of the hardest problems they've got to crack and they're always trying to find shortcuts or compensating measures.

What is the new data mapping as a service?

Baumann: Organizations really struggle with unstructured data. It's still one of the hardest problems they've got to crack and they're always trying to find shortcuts or compensating measures. The reason that it's a hard problem is because there's a lot of data in many different repositories.

What we're trying to do is provide a single pane of glass view of all of an organization's unstructured data assets. It's basically providing the first mile of any sophisticated unstructured data governance program.

In your view, what is intersection of data lakes and data mapping?

Baumann: I'm not really a big believer in the data lake. People really want to manage their data where it resides at rest. What we find is they don't want to move the data. Data lakes, from my perspective, mean you need to move data around. So, we're not doing that and at no point do we move the actual data. All we're doing is enhancing the data and grabbing the metadata attributes.

If we need to connect to a user's data lake we will, but we have our own inventory in the cloud of all the metadata associated with the customer's information.

What's the difference between a data map and a data catalog?

Baumann: It's a really good question, because I think the space is going to evolve fairly quickly over the next couple of years or so. We have contemplated using the term data catalog, as one of our customers had asked us to be responsible for an unstructured data catalog.

What we've learned in recent months is that the data catalog is a thing which is pretty well used within the structured data environments. So, we've moved away from using that particular term.

What has been the impact of COVID-19 on the data mapping business?

Baumann: With some deals that we were working on that were ready to close just at the start of COVID, a number of organizations decided that they needed to take a pause and see what their budgets and priorities would be.

All of them came back, either within a few days or within a few weeks and said, you know what, we can't ignore this, we don't know what data we've got, we don't know where it is and we need to go through this exercise.

This interview has been edited for clarity and conciseness.

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