Data Intelligence in Flux: The Impact of AI with Stewart Bond, VP at IDC
11/13/24 • 42 min
About 15 years ago, organizations knew they needed data governance but faced a branding problem. People hated the term. Stewart Bond coined “data intelligence” to describe intelligence about data and shift the governance conversation – and a category was born. Today, data intelligence represents a $9B+ market.
This concept has given rise to the "data intelligence stack," which includes data cataloging, data quality management, and data product hubs, all of which play vital roles in AI model development.
Looking ahead, big changes are coming. IDC predicts that by 2028, the Chief Data Officer’s role will rival the CIO’s in shaping technology investments. In this episode, Satyen and Stewart dive into the components of data intelligence, the growing importance of data products, and key insights from IDC's recent MarketScape evaluation.
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“We talk about the modern data environment as being highly distributed. Data is all over the place. It's very diverse. There's so many different kinds of data that we're dealing with today. It's also very dynamic. That data is always moving and it's always changing. I think data intelligence as a category, as a capability, there's always going to be that need to have the intelligence about the data that the organization manages in the modern data environment available. That is visible across all the different places the data lives in that modern data environment.” – Stewart Bond
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Time Stamps
*(04:54): What is data intelligence?
*(09:49): The rise of the data marketplace
*(13:01): How will AI impact the data intelligence market?
*(25:54): Is the Chief Data Officer role in trouble? Or is it growing in prominence?
*(38:40): What is the IDC MarketScape?
*(41:14): Satyen’s takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
About 15 years ago, organizations knew they needed data governance but faced a branding problem. People hated the term. Stewart Bond coined “data intelligence” to describe intelligence about data and shift the governance conversation – and a category was born. Today, data intelligence represents a $9B+ market.
This concept has given rise to the "data intelligence stack," which includes data cataloging, data quality management, and data product hubs, all of which play vital roles in AI model development.
Looking ahead, big changes are coming. IDC predicts that by 2028, the Chief Data Officer’s role will rival the CIO’s in shaping technology investments. In this episode, Satyen and Stewart dive into the components of data intelligence, the growing importance of data products, and key insights from IDC's recent MarketScape evaluation.
--------
“We talk about the modern data environment as being highly distributed. Data is all over the place. It's very diverse. There's so many different kinds of data that we're dealing with today. It's also very dynamic. That data is always moving and it's always changing. I think data intelligence as a category, as a capability, there's always going to be that need to have the intelligence about the data that the organization manages in the modern data environment available. That is visible across all the different places the data lives in that modern data environment.” – Stewart Bond
--------
Time Stamps
*(04:54): What is data intelligence?
*(09:49): The rise of the data marketplace
*(13:01): How will AI impact the data intelligence market?
*(25:54): Is the Chief Data Officer role in trouble? Or is it growing in prominence?
*(38:40): What is the IDC MarketScape?
*(41:14): Satyen’s takeaways
--------
Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
Previous Episode
AI and the Workforce: Copilots or Competitors? with Jeremy Kahn, AI Editor at Fortune
The transformative potential of AI is going to affect all of us, regardless of what industry you’re in. While AI has the capability to democratize high-demand professions through specialized copilots, it also presents potential positive and negative societal impacts, including misinformation and political discourse manipulation. Today, we’re taking an in-depth look at the evolution of AI copilots tailored for specific professional fields and the need for critical thinking and transparent AI systems to ensure ethical deployment and improved outcomes in sectors like healthcare and finance.
There’s a growing need for federal guidelines to prevent fragmented AI governance (think the EU AI Act). However, differing approaches to regulations across regions can lead to unbalanced directives. Politics are also influencing this new AI landscape. From potential deregulatory pushes under a Trump administration to sustained regulatory efforts under a Harris-led government, AI regulation will look different depending on who wins the US election. And it’s not just politics, total war is a significant worry when it comes to the use of AI. From military strategies to disrupting democracy, AI has the power to impact innovation, ethics, politics, and society. Satyen sits down with Jeremy to discuss his book Mastering AI, the importance of AI regulations, and the impact of AI on the job market.
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“In the US, we have this issue where the states are starting to take action because of the lack of action by the federal government and I think that's problematic. I don't think you want a system where you have every state with its own AI act and different laws to comply with in every state. I do think we need to have some action at the federal level. When we're going to see that happen, I don't know, because there has been a lot of lack of will. Even though there was some bipartisan efforts in Congress that looked like they were maybe going to pay off last year. I think there's some agreement on both sides of the aisle that there should be some rules and regulation passed around AI.” – Jeremy Kahn
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Time Stamps
*(02:37): The future of AI: A boon for the middle class, a threat to democracy
*(12:18): The case for federal AI regulation in the US
*(20:11): The impact of the US election on AI regulations
*(30:29): What is the Pigouvian or robot tax?
*(36:39): What is total war? How will AI play a role?
*(46:35): Takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/
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Links
Connect with Jeremy on LinkedIn
Order Jeremy’s book, Mastering AI
Next Episode
The Art of Data Leadership: Lessons from Taylor Culver
What does it take for data leaders to deliver real business value? In this episode, Taylor Culver, founder of XenoDATA, shares practical strategies for success, including:
Focus on the right problems: Taylor explains the importance of refining problem statements for actionable, data-driven solutions.
Engage like a salesperson: Actively listening to stakeholders and identifying pain points is key to building impactful use cases.
Adopt a product management mindset: Taylor emphasizes weaving governance and architecture into customer-centric data strategies.
While the path of the data leader is fraught with obstacles, success is possible. Taylor offers time-tested strategies to help data and business leaders alike make a measurable impact.
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“What data leaders should just own is the path to me is probably going to be fraught with failure, but I need to be able to pivot and I need to be agile. I can very much serve myself by adhering to a common set of principles, which I'm going to practice consistently and continually adapt and adjust in the way I engage with my stakeholders and identify their problems and lean in or lean out on data management techniques or delivering certain solutions. It comes down to intent. Do you genuinely want to help people in your business solve problems with data? Do you genuinely want to grow? Do you genuinely recognize that there's not a magic bullet to doing this? Those are the data leaders who will be successful despite facing adversity.” – Taylor Culver
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Time Stamps
*(07:01): The data-business people problem
*(17:50): How data leaders can tackle business problems in 3 steps
*(26:22): Is data a strategic function or an enablement function?
*(33:50): Strategy: Data offense vs. data defense
*(40:45): Data is a people business: the value of trust
*(46:20): Our takeaways
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Sponsor
This podcast is presented by Alation.
Learn more:
Subscribe to the newsletter: https://www.alation.com/podcast/
Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/
Satyen’s LinkedIn Profile:
https://www.linkedin.com/in/ssangani/
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Links
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