Path to power
Generating insights from analytics applied to data has been a strong theme throughout my career. Starting with a PhD, it was highly rewarding to discover new knowledge on disease and cancer through the analysis of biological datasets.
Moving into commercial data science provided an opportunity to investigate business problems across industries. Everything from building next generation recommendation engines, detecting fraudulent behaviours, predicting what consumers want before they even know it, through to interpreting sensor data from aircraft to find optimal flying routes. My passion lies in discovering new business domains, while helping organisations solve problems using patterns and trends in data.
Leading entrepreneurial initiatives, evangelising data-driven business outcomes and highlighting the value of using machine learning and other AI techniques has resulted in the opportunity to lead a multi-talented, multi-cultural team spanning Central Europe, UK and Ireland. My role has included the development of business plans, go-to-market strategies, implementation of efficient delivery-execution and aligning data architectures to business requirements.
Working in collaboration at all levels, from senior executives to delivery consultants, I have become adept at operating in complex environments to deliver business results. I am also a published writer and a regular voice at international conferences and events.
What has been the highlight of your career in the industry to date?
We are embarking on a very interesting age in the data and analytics space. The evolution of compute power and the availability of data means we are able to now utilise advanced analytical techniques in the field of AI to automate intelligence and decision-making at a scale.
We are now entering a time when science fiction can really become reality. Take the Babel Fish from The Hitchhicker’s Guide to the Galexy - an ear, multi-language, sci-fi translation aid. This tool is now a reality with the Google Pixel Buds. I am excited to see these innovations coming in to reality today.
What do you expect 2018 to be like for the data and analytics industry?
For the past three years, the industry has focused on investment in big data platforms that are able to capture rich, complex and voluminous datasets at scale. However, these platforms have failed to create value impact. After all, collecting data does not create value.
By analysing data, the industry can elicit insights that lead to business value. Today, we see a focus on AI methods, such as deep learning and machine learning. These sophisticated techniques make sense of voluminous data. In 2018, the advanced analytics will become more mainstream and industry will move to dealing with analytic ops, the challenge of operationalising analytics at scale.
So - why did you choose data?
With data, the possibilities are infinite. I have a passion for problem-solving and, with data as the raw ingredient, it is possible to create, innovate and solve problems in new ways. The process of taking data - numbers and words, digits and characters - and applying analytical algorithms requires out-of-the-box thinking. This process is both art and science to generate the best solution possible, which requires the combination of my skills in these areas.
I am curious and inquisitive, skills that help me explore and discover insights from data and build stories. I enjoy building data stories that connect with people and help expand understanding into business domains.
What is the best thing about working in the data industry?
The data industry is not discriminatory - every business can benefit from data, big or small. Working in the data industry provides endless opportunities to learn about new industries and have transformational impact, making a difference to every business function.
If you were granted one wish to change something about the data industry, what would it be?
Data needs to be considered and treated like an asset, just like any other physical asset a company may hold, including inventory, stock, factories, buildings or land. All of these assets create financial value for a business, just like data can when used appropriately. Furthermore, putting a value on data and listing it as a key company asset provides a case for securing the data well, ensuring budget to train employees to use data for maximal advantage and investment to allow data to be exploited for competitive advantage. We need methods to assess the value of data based on its freshness, accuracy, completeness and relevancy.
What advice would you give to somebody thinking of a career in this sector?
Start small, scale fast. It is very easy to be attracted to solving the biggest problems and getting immediately stuck into the data and analytics. However, understanding the business domain, keeping stakeholders onboard and knowing the real-world limitations to operationalise insights are essential to any successful project.