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Q&A: Inside data catalog vendor Alation's $110M in funding

Alation co-founder and CEO Satyen Sangani shares why his company is raising money, where the technology is headed, and challenges facing data intelligence and data catalog technology.

Alation announced today that it raised a $110 million Series D round of funding, bringing total funding to date for the data intelligence vendor up to $217 million, with the company claiming a market valuation of $1.2 billion.

The new round of funding was led by Riverwood Capital with participation from new investors Sanabil Investments and Snowflake Ventures, the venture capital arm of cloud data warehouse vendor Snowflake.

Based in Redwood City, Calif., Alation was founded in 2012 with a data catalog technology. Over the years, the company has expanded its platform with data governance and data lineage capabilities to help provide intelligence to users about data. The Alation Cloud Service was launched last month, providing data intelligence as a managed service for users.

Alation co-founder and CEO Satyen Sangani recently spoke with SearchDataManagement about why his company is raising new money, what data intelligence is all about and where Alation is headed in the future.

Why is now the right time to raise Series D for data intelligence, and why is Snowflake involved?

Satyen Sangani, co-founder and CEO, AlationSatyen Sangani

Satyen Sangani: We have been partners with Snowflake for the last year, but then over the last six months, the partnership has really accelerated -- particularly around the topic of data governance, where we found that there was a lot of interest from their end.

We built an aggressive plan for growth at the outset of the year, and then basically decided to go get funding to finance that plan. At the beginning of the year, we had roughly 300 people and by the end of the year, we'll be at roughly 525. This year is certainly a big growth year for us as we are building a standalone, market-leading company.

We see a market that at the very minimum is likely $5 billion in spend, but it could be significantly larger than that.

If you look at adjacent companies like Snowflake, or Salesforce with Tableau, they're still growing at significant scale. So we think that there's an opportunity for us to do the exact same thing.

Where is the intersection between data intelligence and data catalog?

Sangani: The core problem that we solve with data catalog is basically search and discovery of data. There's all this data out there, people can't really use it, people don't understand it, people can't really find it, you need something like a catalog of data in order to use it.

Then there is a group of users that understand the general problem of finding and understanding customer data but now need to be able to fit that into their business flow.

Our sales team spends a lot of time talking about topics like cloud migration, data governance, search and discovery, self-service, analytics enablement, data literacy and data culture, because, you know, people think about those topics. But understanding how to actually get there and implement those capabilities into their environment, that's part of data intelligence.

Where do you see data quality fitting into the data landscape at Alation?

Sangani: Data quality is definitely part of the data intelligence category. We have been really just impressed by the number of new companies that are coming out with innovative data quality solutions. We're really excited to watch that innovation and to partner with many of those players. Two in particular that we work with are Soda.io and Bigeye.

We are going to continue to work with those folks and build the ecosystem in that domain, as customers have lots of different diversity and data quality needs.

What are the key challenges organizations face with data intelligence and data catalog technology today?

Sangani: I think customers are now expecting simplicity and deployments to happen in hours, if not minutes.

Related to that is the concept of automation and machine learning. So that's the ability to automatically tag new data sets, being able to automatically find duplicates and understand which are the most important data sets and what are the least important data sets.

Lots of people claim to do automation, but doing it in a very easy to configure and deploy way is also absolutely critical. There are a lot of problems in the data space, and there are lots of technologies. The challenge isn't the availability of technology, the issue is that technology needs to be available in a matter of seconds. If the technology is there when the user needs it, they will just go with whatever Plan B happens to have been, which is often some form of manual human workflow.

Looking forward for Alation, we're going to be focused on a lot of the ease-of-deployment and usability questions. A big part of that is continuing our investments in the cloud, and making it even more seamless for customers to get on the platform.

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