Big Data London emerging insights

It was great to be at BigDataLDN this week and see the changing landscape. 40% of all sessions had AI in the title. This is a significant shift compared to pre 2023 programmes, where AI titled sessions were typically less than 15%.

The 2026 landscape highlighted a number of shifts.

AI is no longer a track, it is the spine of the conference embedded across every discipline.

Governance and trust are now centre stage. Multiple sessions explicitly focused on trusted AI foundations, AI governance maturity, scaling AI safely, data governance as the prerequisite for AI and observability for AI systems.

Agentic AI is emerging as a major theme. This is the first year agentic AI had a dedicated theatre signalling a shift from the previous experimentation phase to operationalisation.

AI plus organisational transformation is the new battleground asking questions like how do we scale AI safely,  modernise legacy environments,  demonstrate measurable business value, and improve governance without slowing innovation.  This is a change from asking which model to use towards to how do we run an AI enabled organisation. 

Data governance is finally being treated as strategic and it was the strongest governance representation BigDataLDN has ever had.

AI for societal impact is gaining traction with talks now covering climate change and humanitarian impact broadening AI use beyond commercial use cases.

The keynotes were AI centric which created a conference theme of AI first.

I think the BigDataLDN conference has quietly repositioned itself an AI governance, AI strategy, AI engineering and AI transformation conference. 

AI governance seems like the new cloud migration in that it requires a change of mindset. The agenda showed a pattern where

• AI adoption is assumed. 
• AI scaling is the challenge. 
• Governance is the bottleneck. 
• Data foundations are the dependency. 
• Operating models are the differentiator

The conference was packed with people and exhibitors and many people spent their time queueing to get into rooms to get to listen to talks.

 

Big Data LDN 2021 - Data Governance and the essential CDO

Big Data LDN has been running 22 -23 September. There have been some really interesting sessions covering data governance and the CDO role.

Robin Sutara spoke on the analytics paradox - balancing competing demands for agility and governance. Think big, one technology is not a magic bullet and learn to fail fast. 

Start small with one business problem and build upon that. The data quality with adapt and improve to meet needs of each problem being addressed. It is people and culture that change a business. We need to think beyond the technology. 

 

Great session and an important thought for the future to stop talking architecture and focus on business value. It goes beyond economics and needs sustainability.

Data is a hot mess, so lets cook session from Ben Schein mentioned a key point Data Governance is never done and always be open to new ideas. Data governance is a team sport. You need to find a balance between innovation and experimentation, data teams and consistency, usability and scale. He finished with some important areas to consider

• keep data definitions consistent
• don't wait for  perfect data set to arrive
• data quality is essential for good insights
• let people go shopping for the data they needs
• there is no data magic wand
• data governance is a team sport

Another very insightful session from Cindi Howson on data-driven culture: is your organisation a laggard or leader, gave perspectives on the biggest challenges to being data driven. 

Perspectives on the biggest challenge to being data driven is culture (67%) followed by talent and people (22%).

 

To disrupt your culture bring in a change agent, identify relevance (WIIFM) and organise for collaboration.

She talked about CDOs having a short tenure in organizations being an average of 2.5 years. There is an interesting article about that , Why Do Chief Data Officers Have Such Short Tenures? by Tom Davenport, Randy Bean, and Josh King 

Why WIIFM (what's in it for me) for communication, incentives, skills and tribes and role models.

To move forward into this new world there needs to be a transition in organizational design, from that traditional BI centre of  excellence to this embedded design .

Centralize for economies of scale for common data, infrastructure and specialist talent but decentralize when business domain experts are essential to analytics workflow. Ensure that cross boundary communication is ongoing for best practice, synergies and career management. We are looking at a new hybrid model that is transparent and optimized.

She finished with sharing there is a Data Chief Community (TheDataChief.com) . It has podcasts, blog,  roundtables and community newsletter. 

What we learned from 400 data leaders in CDO summer school  session by Carruthers and Jackson highlighted

• Data strategy is multi dimensional not linear
• Governance is being revised but you need to tell the story. It is still a problem but it needs communicating the purpose through strategy.
• They had Scott Taylor talk about data storytelling - keep simple
• Risk - listen, listen and listen more 
• Soft skills are important
• Data Literacy is a spectrum.
• Nurture your community
• Play to your strengths and culture is the biggest hurdle
• Keep policy simple
• There should be a call to arms on Ethics
• Methods can be disrupted, innovative and evoke change
• It is not about technology outcomes

In the summer school they discussed the DIKW Pyramid which represents the relationships between data, information, knowledge and wisdom

Exasol have published the journey to the CDO. 

https://www.thedatadreamer.com/insights/the-journey-to-CDO/