#165 Monetising All Your Enterprise Data to Advance Data Value Creation with HPE's CTO, Stuart Long

#165 Monetising All Your Enterprise Data to Advance Data Value Creation with HPE's CTO, Stuart Long

Author: Felipe Flores August 10, 2021 Duration: 58:54

Stuart Long is the CTO Hewlett Packard Enterprise. In his role, he identifies different product portfolios and pulls together solutions for different customer sets, such as public health, education, finance, retail, mining, and determines how to develop the solutions from HP’s product portfolio across all the different stacks.

In this episode, Stuart tells us how HPE are moving the analytics to the edge, making it actionable with the ability to link data across the organization and across multiple organizations with a new solution out of Europe; Gaia X.  He says that with today’s privacy regulations, it’s now about federating your data and then making that data available to people but still within your control. But you can’t do it alone – you need an ecosystem of partners and products to do that.  And that’s exactly what HPE has done.

They have built a whole range of products to do what they call ‘federated data analytics’. This allows you to look where your data is and start to then understand where you want to analyse that data, and what data flows you need to provide, and how you want to basically store and categorize that data. There are a number of what they call “architectures”, and underneath those architectures, they are developing products that fit nicely within those to enable the customers to look at how to deploy these new systems.

Finally, Stuart tells us what excites him most about the opportunities ahead for Gaia and the data economy as a whole and HPE’s plans for Gaia in the next 3-5 years.  He says the ability to see a whole new range of services be made available very quickly, and different ways of utilizing those services - is what he calls ‘service chaining’. Giving the consumer a way of being able to choose from multiple different providers and customize their own different services and chain them together.

Stuart believes it’s really about developing the whole ecosystem and bringing on different partners.  We will start to see more edge to quarter cloud type environments where organizations will now have a lot more edge processing. Companies will become more and more digital, and services will become more and more digital. He tells us that there will be some interesting opportunities for organisations and with this level of innovation, there is going to be good and bad, but it’s about making sure that you can optimize the good and limit the bad.

Enjoy the show!

Read the full episode summary here.


In a field dominated by discussions of algorithms and infrastructure, Data Futurology carves out a different, crucial space. Host Felipe Flores guides conversations toward the human-centric challenges that ultimately determine whether an AI initiative succeeds or fails. This isn't a technical deep dive into model architectures; it's a series of dialogues about strategy, organizational change, and the practical leadership required to bridge the gap between potential and real-world impact. You'll hear from practitioners and executives who have navigated the complex last mile of deployment, where the real work of integrating technology into business processes and culture happens. The podcast explores how to select the right problems, build effective teams, and cultivate an ethical, forward-thinking approach to data science and machine learning. For leaders, managers, and anyone responsible for steering their organization through the adoption of these powerful tools, Data Futurology offers grounded insights and actionable perspectives. It’s about moving beyond the hype to create sustainable value, ensuring that the rapid pace of advancement in artificial intelligence is matched by thoughtful and effective human leadership. Tune in for a necessary complement to the more code-focused shows in your feed.
Author: Language: English Episodes: 100

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science
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