Data Governance at Elastic: Explained

Starting as a search engine built by Shay Banon in 2000 to help his wife search through a growing list of recipes during culinary school, Elastic has since grown into a legendary technology company, powering search solutions, helping applications run smoothly, and protecting against cyber threats for the world’s most respected organizations.

With a rich history in open source and an offering that’s built on a foundation of simplicity, speed, scale, and relevance, and powered by data, Elastic has high expectations from its Data & Analytics team.

Elastic is distributed by nature, and its team comes from diverse backgrounds. More than diversity in experience, vast differences exist in geography and culture, making it even more important than anything that the team creates and services are relevant and personalized to a spectrum of needs, expectations, and skill sets.

In this week’s newsletter, we spotlight Elastic's approach to aligning its data governance practice with its culture. You can read?the full story here.

? Spotlight:?Aligning data governance with culture

Elastic’s data governance strategy interprets transparency as helping people understand where data is and who owns it. Accountability means ownership and stewardship, and that their stakeholders are accountable for the data they use.

Engagement, their final area of focus, means building a trusting, productive relationship with their stakeholders.

“We need partnership from our business, from our IT partners.?Data Governance isn’t a central dictate that we push upon.?We help with the framework, how to think about governance, how to drive that accountability and transparency to build and grow and to improve the governance of the quality of our data across the board.” – Director of Enterprise Data & Analytics at Elastic

Takashi Ueki, Director of Enterprise Data & Analytics at Elastic joined Atlan at the 2023 Gartner Data & Analytics Summit and led?an Atlan Masterclass?to share how Elastic aligns its data governance practice with its culture, how they evaluated the Active Metadata Management market, and present and future use cases made possible by active metadata.

Choosing active metadata management

Supporting Elastic’s remote work model meant that Takashi’s team would need to pay careful consideration to how their users would adopt a product. While collaboration might be simple in an office, where confirming a data asset’s definition or seeking approval for a change means walking to a colleague’s cubicle, collaborating with a remote workforce demands a thoughtfully constructed user experience.

“When we’re working remote and in a distributed manner, our workplace, our desktop is effectively the applications that we use. If I add another application that’s not integrated seamlessly, it just becomes more clutter on your desktop and it makes that experience more cumbersome,” Takashi explained.

Considering their data governance principles of transparency, accountability, and engagement, and combining their high standard for supporting a remote workforce, Atlan became a clear choice to drive their program forward. “When we looked at it from that perspective, it was really the only one that truly hit all those forms,” Takashi shared.

And with the importance of concepts like partnership and cultural alignment may not appear on an RFP, Elastic found Atlan to be the right partner as they grew their data governance practice. “It was more ‘What are you trying to accomplish as a company?’ And really being a partner in the space,” Takashi explained. “It’s not just ‘Here’s a data catalog.’ But ‘What’s your ultimate goal and objective?’ And helping to make sure we’re able to deliver.”

With a foundation of success in place, Elastic’s future ambitions are clear. Their team’s next frontier with Atlan involves driving ownership and accountability, driving adoption through personalization, and maximizing the return on investment in critical data technology.

The concept of ownership has been a key factor in Elastic’s data governance strategy from the function’s very beginnings, with Takashi and his team identifying data owners, and confirming their agreement to steward their data.

Read more about the present and future of data governance at Elastic here.

Crucial context for business users

Among the most important set of stakeholders for Elastic’s data team are business users. Sharing a use case any data leader could relate to, Takashi elaborated, “You have this new dashboard, you send it to an executive, and they say ‘What am I supposed to be using this for? What are the terms related to? If I have any questions, who should I be reaching out to?”

Prior to Atlan’s arrival, the crucial context was delivered via Slack or emails, with the data team sending a document about the dashboard, if one existed. Business users would then click away to read the document, then back to the dashboard. “It’s not the greatest experience,” Takashi shared.

Now, using Atlan’s Chrome Plug-in, relevant context is available in dashboards directly, avoiding pivoting into new applications or documents, or costly back-and-forth with subject matter experts. “This way, especially for executive business users where they’re not actively going to be in a data catalog, it puts the information at their fingertips, where they work,” Takashi explained.

Read more about the present and future of data governance at Elastic here.

?? ICYMI: Announcing Atlan AI as the first-ever copilot for data teams

Engineers have GitHub copilot. Designers have Ando by Figma. Marketers have Jasper. Writers have Notion AI or Coda AI. What about data teams? Now they have… Atlan AI! ??

We announced?Atlan?AI as the first-ever copilot for data teams, imagine it as the personal assistant for every human of data. The waitlist for Atlan AI is now open and we're doing its first reveal this June (with a live demo that almost feels like magic ??)?Sign up for an invite here.

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