We're in the a Cambrian Explosion of data architectures. In the last two years, dozens of vendors have each championed their own version of ‘the modern data architecture solution’, all claiming to be the future of IT in a data-driven enterprise. The sheer volume of architectures is daunting: Streaming data platforms, data lakes, structured/semi-structured/unstructured data, cloud data warehouses supporting external tables and federated query processing, lakehouses, data fabric, and layers of federated query platforms that offer virtual views of data. All claim to support the building of data products.

No surprise that customers are confused as to which option to choose. 

However, key changes have emerged including much broader support for open table formats such as Apache Iceberg, Apache Hudi and Delta Lake in many other vendor data platforms. In addition, we have seen significant new milestones in extending the ISO SQL Standard to support new kinds of analytics in general purpose SQL. Also, AI has also advanced to work across any type of data. 

What does this all mean for data management? What is the impact of this on analytical data platforms and what does it mean for customers? What opportunities does this evolution open up for tools vendors whose data foundation is reliant on other vendor database management systems and data platforms? This session looks at this evolution, helping vendors and IT professionals alike realise the potential of what’s now possible and how they can exploit it for competitive advantage.

In this executive debate, leading industry analyst Mike Ferguson welcomes leaders from premier software companies to discuss key topics in data management and analytics. Panelists will debate the impact of Generative AI, the implications of key industry trends, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, data and AI governance and sharing, and on-the-horizon issues that companies should be planning for today.

Attendees will learn best practices for data and analytics implementation in a modern data-driven enterprise from seasoned executives and experienced analysts in a packed, unscripted, candid discussion.

In this fireside chat, Mike Ferguson—Europe’s leading industry analyst in data management and analytics—talks to Rob Thomas, Senior Vice President and Chief Commercial Officer at IBM on what IBM is doing to help companies get maximum business value from data and AI.

The discussion will explore what IBM sees as the key things needed to become successful with AI. This includes talking about embracing hybrid cloud computing to support data and deploy AI anywhere; dealing with the challenge of distributed data estate; and exploring integrated data and AI technology stacks and AI assistants that help companies tear down data silos, share data, and quickly build and integrate AI, augmentation, and automation into every part of their business. Finally, it will also explore how IBM is helping accomplish this while maintaining end-to-end data and AI governance.