It’s no secret that AI is reliant on ‘rock solid’ data. However given the vast amounts of data that companies now have spread across a distributed SaaS, on-premises and multi-cloud data estate, many companies they are a million miles away from this. We are also well past the point where people can govern data on their own. They need help and a total rethink is now needed to conquer data complexity and create a high quality, compliant data foundation for AI Success.

In this watershed keynote, conference char Mike Ferguson details what needs to be done to govern data in the era of AI, how companies can conquer the complexity they face, by implementing an always on, active and unified approach to data governance to continuously detect, automate and consistently enforce multiple types of policies across a distributed data estate. The session will cover:

• Current problems with data governance today and why old approaches are broken

• Requirements to dramatically improve data governance using AI and AI automation

• The need for an integrated and unified data governance platform

• Why a data catalog, data intelligence, data observability, AI Agents and orchestration all need to be integrated for AI-Assisted active data governance

• Understanding the AI-assisted data governance services and AI-Agents you need

• Establishing health metrics to measure effectiveness of your data governance program

• Creating a Data Governance Action Framework for your enterprise

• Monitoring the health and security of your data using data governance observability

• Enabling continuous reporting and AI-Assisted data governance action automation

• Implementing data governance AI Agents for different data governance disciplines

In this, the 10th year of Big Data LDN, in its flagship Great Dat Debate keynote panel, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists will debate the challenges and success factors in building an agentic enterprise, the importance of unified data and AI governance, the implications of key industry trends in data management, how best to deal with real-world customer challenges, how to build a modern data and analytics (D&A) architecture, and issues on-the-horizon that companies should be planning for today.

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

In this short presentation, Big Data LDN Conference Chairman and Europe’s leading IT Industry Analyst in Data Management and Analytics, Mike Ferguson, will welcome everyone to Big Data LDN 2025. He will also summarise where companies are in data, analytics and AI in 2025, what the key challenges and trends are, how are these trends impacting on how companies build a data-driven enterprise and where you can find out more about these at the show.

It’s now over six years since the emergence of the paper "How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh” by Zhamak Dehghani that had a major impact on the data and analytics industry. 

It highlighted major data architecture failures and called for a rethink in data architecture and in data provisioning by creating a data supply chain and democratising data engineering to enable business domain-oriented creation of reusable data products to make data products available as self-governing services. 

Since then, we have seen many companies adopt Data Mesh strategies, and the repositioning of some software products as well as the emergence of new ones to emphasize democratisation. But is what has happened since totally addressing the problems that Data Mesh was intending to solve? And what new problems are arising as organizations try to make data safely available to AI projects at machine-scale?  

In this unmissable session Big Data LDN Chair Mike Ferguson sits down with Zhamak Dehghani to talk about what has happened since Data Mesh emerged. It will look at:

● The drivers behind Data Mesh

● Revisiting Data Mesh to clarify on what a data product is and what Data Mesh is intending to solve

● Did data architecture really change or are companies still using existing architecture to implement this?

● What about technology to support this - Is Data Fabric the answer or best of breed tools? 

● How critical is organisation to successful Data Mesh implementation

● Roadblocks in the way of success e.g., lack of metadata standards

● How does Data Mesh impact AI?

● What’s next on the horizon?

A welcome address to the first edition of Data Driven LDN, from Big Data LDN Chair, Mike Ferguson.

In this brief introduction, Mike will outline the agenda for the day, and introduce the key topics that will be discussed.

This session looks at the ever-increasing demand for data and AI, the current challenges slowing development and how companies can overcome these challenges and shorten time to value using generative AI and open tables like Apache Iceberg. It also looks at how this approach makes it possible to transitioning away from siloed analytical systems to a modern data architecture where multiple teams can create reusable data products across multiple clouds and op-premises environments using generative AI in Data Fabric and share that data across multiple analytical workloads. 

In this flagship Big Data LDN keynote debate, conference chair and leading industry analyst Mike Ferguson welcomes executives from leading software vendors to discuss key topics in data management and analytics. Panellists 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, how to manage, produce, share and govern data and AI, and issues on-the-horizon 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 an experienced industry analyst in a packed, unscripted, candid discussion.

In this short presentation, Big Data LDN Conference Chairman and Europe’s leading IT Industry Analyst in Data Management and Analytics, Mike Ferguson, will welcome everyone to Big Data LDN 2024. He will also summarise where companies are in data, analytics and AI in 2024, what the key challenges and trends are, how are these trends impacting on how companies build a data-driven enterprise and where you can find out more about these at the show.

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.