CIO Influence Interview with Daniel Spurling, SVP, Product Management at Teradata

Daniel Spurling, SVP of Product Management at Teradata discussed more about the impact of AI in decision-making for large-scale businesses, steps needed to leverage data for better business outcomes, shifts in data analytics, and more in this Q&A: 

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Hi Dan, with your dynamic career leading product, engineering, and technology teams, share the moments with us that shaped your journey at Teradata. 

Candidly, the moment(s) that probably shaped my career at Teradata was the due diligence I completed prior to joining. Having led large groups at JPMorgan, T-Mobile, and Getty Images, I conducted extensive research before deciding to join Teradata. I found that Teradata’s customer base included the largest firms in every major industry and that Teradata is integral to their critical business functions. In conversations with employees, I discovered a passionate workforce dedicated to solving business problems. Importantly, my research into the product identified opportunities but highlighted its rich history of innovation and advanced thinking, which convinced me to join and commit to continuing the company’s positive legacy.

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How do you see AI transforming decision-making for large-scale businesses? Any game-changing use cases you’ve observed? 

We work with some of the biggest companies in the world at Teradata, and what they’re telling us is that AI is serving as a forcing function, pushing them to rethink their approaches to accessing and consuming data. This extends beyond simply making data accessible for AI; leaders are using this moment to democratize data inside their organizations. Globally, leaders are working to increase access to relevant data – which has previously been siloed – and empower employees to make data-driven decisions based on trusted data products. This transformation requires simplified search and consumption of data, which historically has been spread across dozens of different systems, and bringing it together so that marketing, sales, and services teams, for example, can make decisions to and work with data they know they can trust. 

As an example of trusted harmonized data being a game-changer in AI solutions, last year, we launched an AI offering with Edge Solutions & Consulting. It’s a complaint analyzer that takes in massive amounts of product feedback data from very disparate sources – some structured, most not – and then offers a human-explainable summary of the feedback. Our system dynamically gives prompts and advice to a call center representative, sales representative, or strategic planner, enabling them to make rapid decisions such as next best offer, next best action, or even larger strategy on where and how much to invest in customer improvements. Enabling different teams to harness the plethora of data at this scale, and in real time, was previously impossible for large businesses.

Data is often called the new oil. What do enterprises still get wrong when leveraging data for business outcomes? 

Many enterprises are at the precipice of realizing the value of leveraging data across multiple sources, especially data in unstructured sources and data external to their firm. To remain competitive, companies are effectively using Teradata to harmonize their pristine trusted data with the exploding data sources that were previously difficult to impossible to leverage for real-time decision making. For example, if you’re in the transportation space, you might require real-time cross-referencing of passenger data against uncurated, raw steaming data coming out of the FAA and other sources, while those in healthcare might require inferencing known trusted patient data against a magnitude of raw population health data parameters. There’s so much additional data that data scientists want to access beyond the pristine data in the official corporate data warehouse.

We’re excited to build AI solutions that customers can be confident in, unlocking the value of their data in combination with larger datasets that can drive business outcomes. Our goal is to provide access to a wide array of internal data – in all forms and tiers – and join with external data via our open file formats and catalog support, which is one of the broadest in the industry. Having access to that breadth of data is going to drive real ideation and experimentation about how businesses differentiate even further.

How does Teradata help businesses turn fragmented data into a competitive advantage? 

Teradata is helping businesses on two key levels. First, fragmentation has been hindering data democratization within organizations and holding large-scale businesses back from making the most of their data. Teradata sees open table formats as the natural solution to this challenge, giving customers choice and flexibility. Instead of building new and more complex systems to deliver data products, such as data meshes and data virtualization, an open table serves as a trustworthy, truly open, and connected way to centralize data, enabling businesses to bring their preferred, best-of-breed engines or tools to the data. Open table format support has become a driving force in every architecture decision that we make, and our users benefit from Teradata’s powerful engine and workload management capabilities.

Second, there’s an industry-wide challenge right now: Companies are coming up with amazing ideas for using data but stopping at the idea or experimentation stage. At Teradata, we’ve helped companies figure out how to move from experiment to production and do things with these ideas. One part is helping with data prep so we can make sure you have data you can trust when you start building. Then we help with model creation – including moving from one persona to another, all the way into production. This includes the Data Engineer, the Data Scientist, even the App Developer, who builds an application around that model, and then moving to the operator who manages these models in Production with our ModelOps capabilities. Our goal is to make the process from ideation to production seamless, and we’re already seeing customers who are accomplishing this.

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What’s a recent product innovation at Teradata that excites you the most? How does it enhance business intelligence? 

We’re proud of Teradata’s Enterprise Vector Store, which provides a scalable, trusted foundational technology for the next generation of AI innovations, including agentic AI. Vector stores enable businesses to sort and structure their ever-growing collections of unstructured or semi-structured data, using vectors to represent key details – and relationships between those details – for super-fast AI searching, comparison, and analysis at scale.

Over the next year or so, businesses will increase reliance on agentic AI to autonomously complete complex multi-step and multi-dimensional tasks, using advanced reasoning – reasoning that will depend on a combination of trusted AI and trusted data. Building agentic AI systems that people can trust requires organizations to deeply examine their decision-making processes and maximize transparency, ensuring that customers can have confidence that agentic AI is both performing tasks and delivering results that match or surpassing skilled human levels. This will require a tremendous number of models, and a tremendous amount of vector embeddings. Our Enterprise Vector Store will enable large businesses to efficiently operationalize agentic AI at scale with the required performance and scale.

If you had to predict one major shift in the data analytics industry over the next five years, what would it be? 

Five years? That is a long time in this space! As you know, the world has experienced an AI gold rush, leading even large enterprises to rapidly adopt novel but potentially risky technologies such as generative AI-based text and image tools. Between sketchy data, hallucinations, and biases, users began to question whether they could trust AI-generated results from search engines and chatbots. We’ve all heard the story of under-tested AI solutions submitting inaccurate legal briefs or financial statements to authorities or creating legal exposure to discrimination lawsuits from consumers. While there’s been tremendous industry pressure to move fast on AI, Teradata believes the adoption of trustworthy technologies is even more urgent and necessary.

Over the next five years, I believe enterprises are going to recalibrate their AI efforts around trusted AI, driven by agentic solutions – both public and private – that ensure social, ethical, and legal compliance. While they will continue to develop AI solutions, their need for internal and external trustworthiness will compel them to anchor new launches toward accountability and transparency. This is where I predict there will be a major shift; I predict that individuals and corporations will create and leverage agentic AI solutions of themselves to auto-validate other AI actions and ensure accountability and transparency. In other words, we’ll use agentic versions of ourselves to move from black box data analytics into a new era of creativity and confidence in business and personal decision-making, where people understand AI decisions and can trust it more holistically. Teradata is exceptionally well positioned and ready to serve as the enterprise world’s advisor in this critical transition to trusted AI. 

Lastly, what keeps you excited about driving innovation in AI, cloud data, and enterprise analytics every day?

We’re living in exciting times. Over the last year, we began moving past the early hype stages of AI innovation and started to build on a more agentic approach to AI to be realistic about what we can unlock with the latest technologies. Looking realistically at distinct “now” and “coming soon” horizons has enabled savvy companies to launch AI and GenAI apps today, which are actually able to solve business problems… while experimenting on what will be real tomorrow.

I’m also excited because Teradata keeps building upon an outstanding strategy and key partnerships with other industry leaders. So many people look at us as a reliable data warehouse and best-in-class data platform company, but may not have realized until recently that we’ve been investing for 15 years in AI capabilities, machine learning, and now generative AI. Furthermore, our open and connected ecosystem strategy has led us to cooperate with major players in this space, such as working with NVIDIA on GPU capabilities for on-premise AI with seamless cloud integration. With Teradata VantageCloud and capabilities such as Bring Your Own LLM and the Open Analytics Framework, we enable customers to use the tools they love while getting all of the power and efficiency of Teradata’s engine. It’s exciting to be at the center of it all – helping customers harmonize the data and build the AI solutions that grow their business, brand, and revenue.

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