Analytics
News, events, thought leadership and more.
It's hard to say everyone has it wrong, especially when the statements being made are actually beneficial to your own success, but everyone has it wrong about data scientists. Despite the oft cited article outlining the need for over 190,000 data scientists in the US alone, the reality is that the US economy needs more data artisans than it needs data scientists.
It was a tweet by my good friend Steve Wooledge (@swooledge) over at Aster Data / Teradata who crystalized for me the need for us to ensure the strategic analytics revolution was a mass effort, not just for a select group of PhDs who are too busy to actually impact how organizations perform. Steve got it right because he called out technologists and software vendors for thinking about this in the wrong way. The right way is for us to get the value of data science, Big Data, and any of the other analytic trends happening right now into the hands of the majority who actually make or drive decisions in organizations.
If the analysts press, industry influential and just about everyone else says we need data scientists, why fight it? I don't doubt we need data scientists but the best way to explain this is for us to look at the typical adoption of scientific discoveries. In the normal course of things, research by some incredible minds delivers a breakthrough that is eventually used by someone in a commercial organization to create a product that gets into the hands of some early adopters, before either stalling out at this point or becoming successful with mass adoption. The role of disruptive vendors and users is to circumvent that process to deliver value now and to many, not the few. Think about how Google took deep computer science and used that to revolutionize web search and the advertising industry.
At Alteryx we believe in taking that same disruptive model to get the value of big data and predictive analytics to become a business reality now, not when these capabilities are finally embedded into complex analytic tools like those available from SAS Institute, or IBM SPSS. The way we as an industry will deliver this is not to hire 200,000 data scientists. Instead this will happen when we enable the millions of data and business analysts around the world to evolve their capabilities to get the answer to complex business questions. These evolved analysts (we call them data artisans because they use their craft to answer strategic questions) will combine Big Data with cloud data or corporate data at the point they need it in their analytic process, not when a data scientist's schedule frees up.
We make that possible by delivering easier to use analytic platforms and the power for the analyst to get access to and combine data from any source. Alteryx is doing that today. Check out our thoughts on Humanizing Big Data:
Paul Ross
VP of Product & Industry Marketing
