I am fortunate to have had several roles over the past 15 years, all of which have involved using data and technology to solve interesting problems. I started my career as a cancer epidemiologist at the Office for National Statistics, before moving to Ofsted to head up the schools data and analysis team, where I worked closely with the Department for Education.
I then moved to Dwr Cymru Welsh Water as chief statistician and head of data. At Welsh Water we would pride ourselves on our ability to earn the trust of our customers and I enjoyed the opportunity of using data and analytics to enable the company to be customer centric.
I later moved to GoCo Group (GoCompare), where I became group director of data. It was great to work with a team of like-minded people who were incredibly passionate about data being at the heart of the online business.
More recently I have joined Coats, the world’s leading industrial thread company that operates in some 50 countries, across six continents, where I am responsible for maintaining a class leading data capability and building a deep data driven culture.
I have two proud achievements. Making the 2018 Women in Data/Female Lead “20 in Data and Technology” list, which celebrated inspirational female roles who are helping to transform the world in data and technology. And landing a global position at Coats – a visionary and pioneering global company. I am excited to be joining a world leading manufacturer that is combining deep industry expertise with the practical application of disruptive technology and better use of data to deliver significant, sustainable and measurable improvements.
I often research what other others are doing in the world of data and technology. There are so many great CDO, CIO and CTO leaders who are a great source of inspiration, it would be a difficult task to name them all. However, my experiences to date have taught me that negativity breeds negativity. To stay inspired I like to create a motivating and collaborating atmosphere where ideas can be nurtured.
2019 was an interesting, exciting and shifting year. We have seen machine learning solutions being applied to conservative (and much more regulated) fields like health cases – and, now, taken seriously. For example, machine learning applications in cancer prognosis and prediction.
During 2019, users became more concerned about the handling and ownership of their data, especially due to the countless breaches that happened. And, unsurprisingly Python, the fastest growing major programming language, was the de facto language for data science.
In-memory processing, data-as-a-service (DaaS) and data automation will be some of the hottest topics in data and analytics this year. In-memory computing (IMC) is going to become increasingly popular due to decreasing costs of memory technology, enabling industries to improve the performance of their current applications, whilst creating opportunities for future scalability.
More enterprises will leverage the power that collected data holds and generate an income from DaaS. And more data science tasks will be automated, helping business leaders to efficiently plan and use the right analytics to make the right business decisions.
There are many opportunities emerging from data and tech, bolstering the image of data science as a discipline and illustrating different career pathways in data and analytics. Another opportunity is innovation and innovative uses of data by making it easier to access and use data (where possible) held by both government and businesses, along with keeping pace with the latest data technologies and providing robust protection for people’s privacy rights.
Inflexible technology stack and development processes are big tech challenges. Successful digital experiences are achieved through iteration via the ‘test and learn’ method – where features are regularly added, measured, adjusted and pruned. However, from my experience, it can be too difficult for companies to take this approach when, for example, development processes involve quarterly releases. Leveraging agile processes and technologies that support frequent, if not continuous, integration and product releases are key behaviours that lead to effective digital results.