AiThority Interview with Aaron Kalb, Chief Data & Analytics Officer at Alation
Hi Aaron, please tell us about your role and the team/technology you handle at Alation?
Part of my job as Chief Data & Analytics Officer (CDAO) is to build and lead our internal Data & Analytics team, where we refine raw data into value-added information assets (e.g., views, dashboards, machine learning models); provide measurement and insights to colleagues so they can optimize daily decisions and strategic choices; and empower our teams both with education and self-service resources so they can interpret and analyze data effectively and autonomously.
And since we’re a data company, I also have an incredible opportunity to network and build relationships with CD/AOs across our customer base, in industries ranging from insurance, to pharmaceuticals, to financial services, consumer packaged goods, utilities, manufacturers, and more, serving as a sort of clearinghouse for best practices as we all strive to instill data cultures in our respective organizations.
What is the most exciting part about working in the Big Data as Service industry? What do you like the most about the technologies used to create and deliver best CX in the Big Data industry?
You might not expect to hear this from me, but I actually think “data” is boring. I think the world, however, is infinitely interesting and data is the way to truly understand what’s happening in the world. Alation’s data intelligence solution helps the human beings at our customers actually get value and insight from their data, to understand their businesses, employees, customers, etc. and do their job better. That’s what I find thrilling.
From a technology perspective, I studied AI in grad school and worked on Siri (Apple’s voice assistant), so I can geek out on ML about as much as anyone in the industry. But technology is a means to an end, and it will only have a positive impact when wedded to an understanding of human psychology and great design thinking. That’s where I like to play.
What is Alation and what are your top offerings / solutions?
Alation is the leader in enterprise data intelligence solutions. Alation enables organizations to find the right data to use at the right time, with confidence. Through its collaborative and user-friendly solution, Alation helps organizations become more data-driven by enabling data search & discovery, data literacy, and data governance at the point of data consumption. Alation empowers organizations to make decisions based on trustworthy data that impact growth, innovation, operational efficiencies, and customer satisfaction.
How do you compare Big Data and AI Ops trends in pre-covid days with what’s happening now?
The pandemic majorly disrupted virtually every organization, albeit in different ways. Whether you’re a streaming entertainment company experiencing a surge in demand from people stuck at home, or a hospital overrun with patients in need, or an appliance manufacturer simultaneously experiencing supply chain disruptions and tons more orders, your business today looks very different than it did 14 months ago.
And those sudden shifts had a few big implications for data:
- Analytics became essential. When this month is like last month, you know what’s happening without looking at a dashboard. When the world’s upside down, you need data to have even the faintest idea of what’s happening.
- AI & ML models trained on historical data may not make accurate classifications or predictions for this new normal.
- However, organizations need algorithmic automation more than ever given all the shifts in the economy.
It’s a very interesting time, to say the least.
Which industries have been leading versus lagging in the adoption of AI ML capabilities? How do you enable such companies to come to terms with modern data science trends?
Gaming makes for an interesting case study at the forefront of AI/ML. Because they’re trying to understand customers (i.e. players) and predict behavior in a virtual world they’ve constructed, game developers don’t have to finish a “Digital Transformation” to have data on every single step/action/move people make. And when you monetize by selling virtual goods, a perfect understanding of demand can be directly converted into revenue since you have an infinite and infinitely flexible supply.
It’s interesting to watch smart people in more reality-constrained verticals trying to do similar things in more challenging contexts—for example, how retailers try to use receipts and WiFi hotspot pings to model real-life shoppers like VR avatars.
Tell us more about your recent AI biases report and how it influences the ability of an organization to better use data science / data management?
As an overview, our third installment of the quarterly Alation State of Data Culture Report highlighted the data challenges enterprises face as they continue investing in AI. The report goes beyond assessing organizations on the state of their data culture and key business drivers for data and analytics, by including an in-depth look at how organizations are deploying AI and the challenges inhibiting optimal results from those initiatives.
Skewed or unrepresentative training data leads to biased results. This is a fact, and the world is fast discovering the impact data bias has had in a wide array of machine learning applications, from criminal justice to healthcare to business. As it relates to biases, the survey found that nearly nine out of ten respondents are somewhat or more concerned about inherent biases being used in AI to produce discriminatory output.
Enterprises that have successfully deployed AI are more apt to be very or extremely concerned about data quality (50%) versus those who have not yet deployed AI (34%). Those data leaders who have deployed AI also cite incomplete data as the top issue that leads to AI failures. This is because when you go searching for data to create the models—be it for product innovation, operational efficiency, or customer experience—you uncover questions around the accuracy, quality, redundancy, and comprehensiveness of the data. Those who have deployed AI obviously understand this, which is why they cite cataloging data for visibility and access to available data (38%) and the ability to crowdsource information (38%) as two of the top three ways to combat bias, just behind better modeling skills (44%).
Hear it from the pro: Who / which team owns the success and failure of AI journeys in digital transformation operations?
The greatest successes I’ve seen have emerged from really collaborative and productive partnerships between technologists and subject-matter experts close to the real business problems and opportunities. Any given business unit will never be able to hire and retain the same kind of AI talent that a centralized team of uber-nerds (like me and my team, I’ll admit with pride), but such a team will produce high-tech-yet-useless output without a liaison to the real world.
An advice to every CIO / CISO in 2021:
Ignore my advice and trust the data 😉 Your business is so different from mine, and from yours last year, and it’s going to change so fast as the economy asymmetrically thaws all over the world—nothing I could say will be stably applicable. The key will be listening to the data as the story changes and responding with agility.
Tag a person from the industry whose answers you would like to read here:
Minna Kärhä brilliantly applied artificial intelligence to a deftly consolidated data-set to make accurate predictions and improve the customer experience at Finnair. You should definitely have a chat with her!
Thank you, Aaron! That was fun and we hope to see you back on AiThority.com soon
Aaron is co-founder and CDAO at Alation. He has spent his career working at the intersection of humans and technology to help people satisfy their curiosity and make more rational decisions. As CDAO, his mandate is to promote data culture and data-driven decision-making within the company and around the world. Prior to Alation, he worked on Siri at Apple in the Advanced Development Group. He holds Bachelor’s and Master’s degrees in symbolic systems from Stanford University.
Alation pioneered the data catalog market and is leading its evolution into a platform for a broad range of data intelligence solutions including data search & discovery, data governance, and digital transformation. Nearly 200 enterprises drive data culture, improve decision making, and realize business outcomes with Alation. More than 100 organizations, including eBay, Munich Re and Pfizer, leverage the Alation Data Catalog. Headquartered in Silicon Valley, Alation is funded by Costanoa Ventures, Data Collective, Harmony Partners, and Icon Ventures.