Atlan emerged seemingly out of nowhere to change into one of many preeminent suppliers of knowledge catalog options. However the path to success for Atlan didn’t arrive spontaneously, and was the results of arduous work and expertise of CEO and co-founder Prukalpa Sankar, who can also be a BigDATAwire Particular person to Look ahead to 2025.
BigDATAwire: First, congratulations in your choice as a 2025 BigDATAwire Particular person to Watch! Again in 2012, you and your eventual Atlan co-founder, Varun Banka, had been constructing a giant knowledge platform for prime minister of India. Did you ever suppose that work you had been doing at SocialCops would result in a profitable firm?
Prukalpa Sankar: Completely not – and but, trying again, it feels virtually inevitable. On the time, we weren’t optimizing for fulfillment. We had been optimizing for influence. We didn’t got down to construct an organization – we got down to clear up significant, high-stakes issues.
From counting buildings with satellite tv for pc imagery to converging 600+ messy knowledge sources, SocialCops gave us a front-row seat to a number of the most painful, chaotic, and guide knowledge challenges on the planet. And once you reside by way of that ache lengthy sufficient, you both give up – otherwise you construct one thing higher. Atlan was born out of that “sufficient is sufficient” second.
We weren’t attempting to construct a startup. We had been simply obsessive about fixing the issue the fitting method.
BDW: Atlan has change into one of many high knowledge catalog suppliers over the previous few years, and was the far and away chief in the latest Forrester Wave for Enterprise Knowledge Catalogs. What do you attribute that success to?
PS: Our largest aggressive benefit is care.
At Atlan, we function with a core precept: prospects > firm > workforce > me. That hierarchy shapes each choice, each line of code, each roadmap debate. We actually care – about fixing actual issues, about making our prospects heroes of their organizations, about being an actual accomplice of their journey.
This degree of empathy has helped us construct belief. It’s why we’ve constantly been the top-rated resolution throughout industries and buyer overview platforms. It’s additionally why we’ve been capable of innovate forward of the curve.
We had been the primary to launch Atlan AI. The primary to operationalize Knowledge Mesh and Knowledge Merchandise in a catalog. We pioneered Energetic Metadata and redefined the class – not as a documentation device, however as a residing, respiration cloth of the trendy knowledge stack.
We didn’t simply discuss “shifting left.” We constructed workflows that combine metadata natively inside engineering instruments. Each a kind of bets got here from listening deeply and caring intensely.
And that care shall be our edge going ahead. As our prospects face the largest shift of their careers on this new AI-native world, they received’t want simply one other vendor. They’ll want a accomplice they’ll belief. We plan to indicate up with the identical degree of care, empathy, and innovation they’ve all the time recognized us for.
BDW: Knowledge governance is difficult. What’s the one most necessary factor that practitioners do to enhance their odds of success, or no less than decrease the ache?
PS: Begin with the enterprise drawback. Not the expertise.
After working with 200+ knowledge groups, we’ve constructed one thing we name the Atlan Method – a set of hard-won classes about what truly makes governance succeed. Not simply the tech, however the folks, this system, and the working mannequin.
Most governance packages fail for one in all three causes:
- They by no means rise up and working.
The metadata stays dry. Implementation is just too guide. It’s too arduous to take care of. That’s why we constructed Atlan to be automation-first and to shift left – deeply integrating into the info producer workflow. Governance shouldn’t be a one-time setup. It needs to be a sustainable, long-term behavior – a part of the way you construct and ship knowledge merchandise every single day. - They by no means get adopted.
That is the place our change administration philosophy kicks in: don’t pressure it. Take expertise to your customers – don’t carry your customers to the expertise. That’s why Atlan exhibits up the place your workforce already works: inside Slack, Microsoft Groups, BI instruments, and knowledge warehouses. We meet folks the place they’re, not the place we want they’d be. - They’re not future-ready.
Change is the one fixed within the knowledge ecosystem. Two years in the past, no one was speaking about vector databases. Final yr, they had been in every single place. This yr, the dialog has already moved on. Governance techniques can’t be brittle. That’s why we’re constructing a completely open platform – so governance doesn’t sluggish groups down, it units them free.
On the finish of the day, we consider governance needs to be invisible. It shouldn’t really feel like management. It ought to really feel like enablement. Embedded within the workflow. Constructed for actual people. And all the time evolving.
BDW: Atlan’s technique is to function the metadata management aircraft, sitting above the info device stack to manipulate knowledge by way of metadata. That’s not how knowledge practitioners are accustomed to doing all the pieces inside their device. What’s the secret to altering these previous habits?
PS: The key is straightforward: you don’t change habits—you design round it.
Certainly one of our earliest classes at SocialCops was that individuals revert to what’s best. You possibly can’t brute-force new workflows. So as a substitute of attempting to combat that, we constructed Atlan to be the connective tissue – not a brand new silo. Our philosophy is to meet folks the place they’re, not the place we want they had been.
That’s the place Energetic Metadata is available in. Most metadata platforms act like passive libraries – nice for documentation, however disconnected from actual work. We flipped that mode. Atlan prompts metadata throughout the stack – embedding it into instruments groups already use: GitHub, Slack, Groups, dbt, BI instruments, and knowledge warehouses.
We’ve introduced metadata into engineering workflows, the place producers truly construct and ship knowledge merchandise. We’ve helped knowledge customers discover trusted context proper contained in the instruments they already use. That is what we imply by shifting governance left – governance that seems like a characteristic, not a friction.
As a result of on the finish of the day, “Metadata isn’t a layer you add. It’s the muse you construct on.”
BDW: GenAI instruments and LLMs are proliferating in enterprise knowledge stacks. What difficulties do these new instruments and applied sciences pose to knowledge governance?
PS: We’re not in a digital-native world. We’re coming into an AI-native one.
Probably the most fascinating factor about LLMs is that they now perceive language – however they don’t perceive which means. Solely people can educate that. And as LLMs begin doing extra of the work people as soon as did, one query issues most: are you able to belief it?
Are you able to belief the info that skilled the mannequin? Are you able to belief the mannequin that produced the output? Are you able to belief the AI-generated motion that impacts your enterprise, your prospects, or your model?
That’s the place governance steps in. Not as coverage enforcement, however as a system for context and belief.
Within the AI-native enterprise, governance isn’t a back-office perform. It’s a frontline enabler. The businesses that transfer quick and construct belief would be the ones that win. However that’s solely attainable if governance evolves into an clever, embedded, real-time functionality.
We consider that is governance’s leapfrog second – an opportunity to maneuver from being a value middle to a aggressive benefit. As companies rewire their merchandise and processes with GenAI, the true query received’t be “Can we do that?” Will probably be “Can we belief this?”
That belief must be systemic. It may possibly’t cease on the knowledge. It has to circulation by way of the complete lifecycle of selections, fashions, and automation. That’s the function of Energetic Metadata as a semantic layer: making which means machine-readable, making governance invisible, and serving to AI act with context and care.
And that’s why “Within the AI-native period, governance isn’t a blocker. It’s the unlock.”
BDW: What are you able to inform us about your self outdoors of the skilled sphere – distinctive hobbies, favourite locations, and so forth.? Is there something about you that your colleagues is perhaps stunned to study?
PS: I’m the one Prukalpa on the planet – actually. My mother and father say they considered search engine optimization earlier than Google existed, and actually… they weren’t mistaken.
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