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What is Data Science anyway you might ask?

Last week I wrote on how to become a Data Scientist, posting a collection of resources and techniques to get anyone interested started on that career path. It’s worth clarifying what the role actually is and what the future might look like in this currently popular career.

Data science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, data mining, and predictive analytics, similar to Knowledge Discovery in Databases (KDD).

Wikipedia’s definition is as good as any highlighting key activities currently undertaken by a variety of roles including that of a Data Scientist – Data Analysis, Statistics, Data Mining, Predictive Analytics. What is happening in the industry as our dependence on data grows is a rapid investment and emergence of technology to perform all of those functions with software, tools, services and platforms turning up every day. All of this investment and development is also happening to a field that is no longer silo’d, is becoming ubiquitous and embedded into every industry, every discipline fulfilling our need for data-driven decision making.

Salacious blog title aside the hypothesis I raise is a valid question, where technology and automation of thinking tasks are developing at a rate outpacing that of a human’s capability is there a future whereby those thinking tasks will also be replaced? It would seem that the emergence of cognitively oriented technologies will change the nature of Data Science at some point in the future. Initially however, I would suggest it will instead support and embed the function.

IBM Watson

ibmwatsonThe loudest voice in Cognitive Computing is IBM, perhaps they have the biggest marketing budget? but Watson is everywhere in my news feeds, adverts served up to me, customers asking questions and speakers at events I attend. Self-promotion aside it would seem IBM are making an impact, this article “In the Future will there be any work left for people to do” written 2 years ago now starts us on the Future of Work discussion with a range of predictions as to how IBM Watson will replace jobs – many of which have started to happen. Quick Watson things you should know just in case their marketing missed you:

So when KPMG announce they have a new employee named Watson the hypothesis starts to feel even more real “KPMG has made a new hire to help its knowledge workers innovate: an IBM computing system named Watson.” KPMG themselves admit in the article it is unlikely Watson will directly displace humans…… immediately.

Humans need not apply

Let’s think about this more broadly than just Data Science for a moment, technology is changing our workloads, automation is driving down costs and enhancing our buying power as consumers. The composition changes in our workforce have been well documented through the ages, we can only speculate as to what roles humans will play in the future given the pace of change we have seen in the last 20 years – remember life before the internet, iPhones, self-driving vehicles, and online shopping? This all poses the larger question of whether we can invent new jobs quickly enough to maintain a gainfully employed human workforce – something for another discussion. 

This is a great thought provoking clip on the Future of Work* which moves beyond automation or manual roles, the economics of automation vs human labour, self-driving cars, software bots, doctor bots, reduced demand for human mental labour and other things to come.

  • I really wish one of our political parties hadn’t latched onto this phrase (future of work) recently, means I need a new one.

Humans will still have roles, different ones we don’t yet understand fully. So like Medicine, Law and Professional Drivers – Data Science will evolve and the role of those working in analysis, prediction, statistics and data mining will also change leveraging increasingly impressive technology. Does pose something for us to all think about, Vic. 

Victoria MacLennan is a reformed techo from the data and information management world – who now focuses on creating jobs and opportunities.

She is passionate about Open Data, Data Privacy and Governance so will blog on those topics occasionally. 

You can read all of Vic’s blogs here.

Don’t forget, we can train your team in the art of agile business intelligence at any time!

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