UPDATED 17:30 EDT / DECEMBER 28 2018

BIG DATA

Q&A: How self-serve analytics are made

An unprecedented availability of data surging from billions of endpoints gives businesses valuable information in key decisions. But complex data repositories can limit accessibility across an organization and curb collaboration, and can squelch innovation opportunities for employees lacking comprehensive data literacy.

That’s why Stephanie McReynolds (pictured), vice president of marketing at Alation Inc., is working to remove the boundaries created by knowledge gaps in digital business and foster more productive relationships between humans and machines with Alation’s collaborative data catalog and querying tools.

McReynolds sat down with with Peter Burris (@plburris), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at theCUBE’s studio in Palo Alto, California. They discussed how Alation is building communities to achieve data-driven outcomes utilizing data catalog technology. (* Disclosure below.)

[Editor’s note: The following answers have been condensed for clarity.]

Let’s talk about Alation. What’s the update?

McReynolds: We went from initially about seven production implementations to now over a hundred organizations using Alation. We’ve seen organizations move from hundreds of users to thousands. It’s exciting to look at our origins with eBay as our very first customer, who’s now up to about 3,000 users. All of them now have a large population using a data catalog to drive self-service analytics and business outcomes.

What kind of outcomes are folks trying to achieve? How are you seeing your company tie the use of catalogs to these outcomes?

McReynolds: Customers are undertaking transformative change, not just in the tooling and technology their company uses, but also in the organizational structure and data literacy programs driving towards real business impact. [Our] customer Pfizer [is] using the Alation data catalog in an integrated analytics workbench that is helping with new drug discovery. [For] ill individuals, they’re now able to use machine learning and algorithms informed by the data catalog to catch a slight deviation from the norm and deliver drugs appropriately.

Munich Reinsurance [supports] first line insurers by re-insuring them. They’re founding business units for new types of risks in the market [and] leveraging the data catalog as a collaboration platform between actuaries and individuals that are knowledgeable in the business to define the data products that could support entirely new business units, like cyber crimes, and invest in those units.

Becoming more data driven requires significant organizational change. Are you seeing communities form around achieving these outcomes and utilizing these types of technologies to accelerate business change?

McReynolds: At an organization like Munich Reinsurance or Pfizer, there’s an internal community using the data catalog as a collaboration platform, a kind of social network for the data nerds. If I am a brand new user of self-service analytics, I may not know how to write a sequel query yet [or] validate data for quality or consistency. I can now go to the data catalog to find trusted resources of data assets.

Sponsors of the data at these organizations are starting to share best practices with one another, and there has been a demand for Alation to help catalyze the creation of communities across different organizations. We kicked off, within the last two months, a series of meetings called RevAlation.

Folks are not talking just about how they’re using the technology; they’re talking about how we improve the data literacy of our organizations, how we close this gap between having access to data and trusting the data and getting folks who maybe aren’t familiar with the technical aspects of the data supply chain comfortable in moving away from intuitive decisions to data-driven decisions.

Alation’s been on this path for a while. Not too long ago, you came on theCUBE and talked about TrustCheck. Is [RevAlation] part of the journey you’re on to try to get people to see this relationship between data-driven business and knowing more about your data?

McReynolds: It absolutely is. It’s a journey to get organizations to understand the power they have internally within this data, which is in part organizational, but in part psychological. You’ll continue to see us invest in features like TrustCheck that highlight how technology can make recommendations, can help validate and verify what the experts in the organization know and propagate that more widely. Then you’ll also see us share more best practices about how to create the right organizational change and how to impact the psychology of fear that we’ve had in many organizations around data.

When we go into organizations and talk about adopting a data catalog, it’s as much about how our products support psychological comfort with data, as well as how they support the actual workflow of getting that query completed. Not just, “How do you execute a software program that supports workflow?” but, “How do you think about how the data consumer actually adopts best practices to use data in a more confident way?”

Algorithms need to take input from a lot of different human perspectives and optimize an outcome using technology as a support structure. Alation is the Google for your data in your organization. Evolution in data needs to happen for our organizations to broadly see analytic-driven outcomes, just as in our consumer or personal life Google had to show us a new way to evolving to a kind of answering machine on the internet.

Watch the entire video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s CUBE Conversations. (* Disclosure: Alation sponsored this segment of theCUBE. Neither Alation nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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