I started in computer engineering and advanced research, including projects on natural language processing and use of large databases. Back in 1996, I presented a data engineering paper on preparing data for analytics with a “very large dataset” of 60Gb. Tiny by today’s standards! I moved into more mainstream data at Centrica, where I owned the customer data warehouse and led the group data governance team. A lot of the basic principles we applied (for example, good data quality and aligning data initiatives with business value) are still true today. A number of the people I worked with then are now on the DataIQ100, so we must have been doing something right. I’m what some people describe as a “purple person” - I understand tech and am able to translate it so it makes sense to business people. That’s why I’ve been able to work in consultancy (BAE Systems Applied Intelligence and EY), technology companies (Teradata) and end-user organisations (Centrica and now Co-op). Currently, I’m again combining a group data governance role with providing the data engineering to support data science.
The best times are when you get to use data to make a positive change which impacts customers or wider society. I’ve been very lucky to work with some cutting-edge data technologies which have resulted in criminals being captured and customers being protected from personal loss and fraud. Most recently, I gain great pleasure from working with The Open Data Institute (ODI). Everyone there is so optimistic about the potential for doing the right thing with data. I always come away from meetings with them in a positive frame of mind.
I would try to reassure the undergraduate version of me that, in 30 years’ time AI, would be talked about on the mainstream news and therefore it wasn’t just a theoretical topic with no practical use. (It was a hard slog back in the day).
In 2018, we had a perfect storm of data protection law improvements and data protection scandals. I’m surprised that there hasn’t been more demand from the public to ensure that their data is managed better and used carefully. I’m sure that we will get to a place where the public demands more and where being open and transparent is seen as an important differentiator by consumers. Hopefully, that day isn’t too far away.
The hype around AI (and data more widely) means that start-ups keep releasing new ML solutions with very little consideration around how data will be managed in those tools. Getting value from a model is more about building a repeatable process of test-and-learn, not around developing one use case in a PoC. I’m hoping that 2019 will be more about embedding ML into the business - certainly something I’m working on.
Its a very exciting time to be in Manchester. There is lots of digital innovation and tech start-ups in the city. This means that there are lots of good people motivated to move to the area, but also lots of competition. We are supporting local meet-ups and sharing via blogs and social media. Being open benefits awareness of the Co-op as an employer, but also raises that awareness with existing colleagues.
Open and trustworthy data will help us combat the lies and half-truths which seems to plague our society at the moment. (That may take a little time…)