At the recent Big Data LDN conference it was clear that the pace of change in the data ecosystem is accelerating – and the winners are those helping businesses unlock value without requiring expensive business transformation programs.
Toby Fitzherbert shares his standout takeaways from the sessions:
1. Creating a trusted view of your business
It wouldn’t be a LinkedIn post in 2025 without mentioning AI. According to Gartner, 75% of organisations rank AI-ready data among their top five investment areas. However, if AI is going to be used to make decisions in your business, there’s no way you can do it without trusted and reliable data. This is where data management tools are becoming a necessity – context is essential with AI, and if you aren’t able to make your structured, semi-structured and unstructured data readable and accessible, you risk bad data infrastructure creating bad data-led decision making. The benefits of quality data management tools are a single source of truth, better data governance, and standardised formats that are then easy to overlay with AI and analytics that drive good decision making within organisations.
2. Data governance
As organisations scale their data ecosystems, the need for robust data governance becomes increasingly critical. Compliance and consistency require a clear framework, and the right people and processes in place to manage data as a strategic asset. This includes establishing data quality programmes with common metrics and issue-resolution protocols; fostering data literacy through glossaries, catalogues, and training; and implementing secure, compliant access policies. Without such foundations, data and AI initiatives risk amplifying silos, biases, and operational complexity. To truly unlock the value of data, businesses must also elevate data leaders to the senior management table, ensuring governance remains central to strategic decision-making rather than an afterthought.
3. Innovation
Innovation in data and AI begins with ambition. Setting bold goals that challenge conventional thinking and push the boundaries of what is possible. True progress emerges when organisations are willing to experiment, iterate, and occasionally fail. Many successful innovators take a “build first, optimise later” mindset. Crucially, innovation must be guided by a deep understanding of customer needs. Engaging directly with customers throughout the development process ensures that new solutions not only leverage cutting-edge data capabilities but also deliver tangible value.
4. Organisational alignment
Achieving alignment between business strategy and internal data initiatives is essential for driving meaningful impact. Aligning data outputs with organisational objectives means you can move beyond isolated projects toward scalable, value-driven data products. A structured approach can help: 1) align on clear objectives; 2) identify measurable metrics to track progress; 3) design, build and validate data products; 4) focused efforts to drive adoption across the organisation; and 5) measuring impact that ensures accountability and continuous improvement. Embedding a process likes this helps ensure every data initiative contributes to long-term growth.
It’s an exciting time to be investing in the data space – keen to connect with others in the sector to hear your thoughts.
