This blog post is part of the Big Data Week Speaker interviews series. In this article, Kim Nilsson, CEO Pivigo, shares her thoughts on the impact of big data in business and how you can get started with data science.
- The data scientist profession is currently very high in demand, and it will remain so, at least for the near future. How does one make the leap from Data Analyst to Data Scientist?
That is incredibly difficult to answer, because both job titles are so unprecise! I know people I would classify as data scientists work in data analyst roles and vice versa. If we are talking about the transition from “traditional analytics and BI” to “data science” (as in predictive analytics and machine-learning), then I think there are two areas to consider:
1) Technical skills, most likely in a more hardcore programming language such as Python, as well as machine-learning and advanced data querying skills.
2) The scientific approach to a problem; how to set up a hypothesis, prepare the data, run the experiment and evaluate the outcome. Data science has the word ‘science’ in it for a reason!
- How did businesses adapt so far to the impact of big data?
Not enough! I have definitely seen an upswing in activities and projects in the last few years, but we still have a long way to go. Some sectors are ahead of others (notably retail and media) and some companies are further along than others. I recently presented at an IoT showcase with Centrica. They are miles ahead of the other utility companies in the digital transformation.
- Why is it important for organisations to become data-driven?
They have to do it or they will lose their competitive advantage. It is like during the industrial revolution; those companies that did not buy machines, and continued to rely on hand labour, all disappeared, and only those who dared to invest in innovative methods to become more efficient and profitable would survive and thrive.
- What are the challenges encountered when trying to leverage data?
Oh gosh, where to start?
1) Access to data in the first place. This includes both having actual data to work with, and having access to it. Sometimes organisations have data, but it is scattered everywhere, in different formats and with different owners. That can be a nightmare to collect to work with.
2) Asking the right question from your data.
3) Access to people and talent. This is, as we know, a big problem.
4) Commitment within the business to listen to, and implement what the data team finds.
5) Budget, and the problem of trying to assess the return on the investment for management.
5. How do you see the industry evolving over the next few years?
Rapidly. As I said, we already see encouraging signs compared to previous years and as more case studies are published, and access to talent becomes easier, I expect an explosion in projects and hiring. This is a very fast growing industry, and I believe growth will only accelerate going forward.
- How do you consider the new automation wave and self-teaching AIs will impact the world?
I see data and AI changing the world. Many industries will be disrupted by this, and it will not be easy for our society to go through. There will be jobs lost, but others gained. The big challenge for society is re-training individuals, and not losing a generation of workers. Take examples like the logistics and transport industry. When self-driving cars mature we will have millions of jobs lost. But it has to be. Millions of jobs were lost in the industrial revolution, but it brought incredible leaps in prosperity and health to society as a whole.
- Tell us a bit more about your topic at the BDW2017 London Conference. Why did you choose this particular subject?
I have seen so many companies struggle with the “getting started” bit. It doesn’t have to be hard, we can learn from each other, and we can bring about that golden future sooner. I am passionate about supporting companies to become more data driven, because of the benefits that bring to all of society. Hence, I want to share the experiences we have had, running 100 short and agile data science projects with companies of all sizes and from all sectors, and inspire other organisations to get started too.
- Who do you think should attend your talk at Big Data Week? Why?
My talk is aimed at business leaders and managers who are curious about data, or maybe just getting started. I will give them concrete tools and case studies that will help them in their progression from data curious to a data leader.
Kim has a background in science, with a PhD in Astrophysics and also an MBA from Cranfield School of Management. She is the co-founder and CEO of Pivigo – the Data Science Hub. Pivigo is a data science marketplace and training provider based in London. Founded in 2013, Pivigo aim to improve the employability of PhDs by training them as data scientists, which is a highly in-demand commercial skillset. Kim with her team at Pivigo are passionate about bringing businesses and scientists together to harness the value and opportunities in data, by bridging the gap between the two fields using their bespoke training programme S2DS; Europe’s largest data science programme. Since the launch of Pivigo, Kim has been named a Rising Star among the Top 100 Influencers of Big Data in the UK and she is also the chair of a TechUK Big Data skills working group and member of the Government’s Data Skills Taskforce.
Don’t miss Kim’s talk at the upcoming Big Data Week London Conference, on October 13. Get your Early Bird ticket today!