Last week I wrote about the increasing demand for analytically-skilled, sophisticated statisticians by all sorts of companies looking to take advantage of our increasingly data-driven world. This past Wednesday, the New York Times published another piece yet again highlighting this trend:
As suggested by Daniel Pink’s assertions on the rise of a right-brained working elite, the ability to extract stories from a world of increasing and abundant data will be increasingly critical to many industries. Indeed, the opening of U.S. federal government data at data.gov (and the appointment of Sir Tim Berners-Lee to similarly open the UK’s data archives) implies a new societal and cultural importance for data wranglers. (my emphasis)
The article also included some great links for those looking to get started examining this new trend. They include:
- The recently published book “Beautiful Data” brings together essays some of the world’s most cutting-edge data practitioners — such as Stamen Design — on subjects as diverse as DNA analysis, crime maps and crowdsourcing.
- Ben Fry’s PhD thesis “Computational Information Design,” which outlines the need for a new field based on multiple disciplines.
- The post “Three Sexy Skills Of Data Geeks,” which explains statistics, data munging and visualization — or studying, suffering and storytelling, as the author jokingly suggests.
- Blogs such as Dataspora and Flowing Data.
Some people may be asking what the big deal is. Statisticians have been around forever and their techniques have become more sophisticated over time. The big deal is that it isn’t just about statistics and crunching numbers. It is about combining multiple disciplines–such as statistics and graphic design–at a time of unprecedented data accumulation so as to glean better insights through the collection, analysis, and visualization of data. Most companies claim to have a focus on ‘analytics’, but in my experience this term and its sophistication in a business setting varies widely. Getting the most out of data requires leadership to think deeply and strategically about what kinds of data would be most useful, what kind of measures most illuminating, and how potential insights gleaned from that data might change their go-to-market strategy as well as R&D. This should be correlated with a serious commitment to creating the necessary infrastructure (i.e. processes, systems) for collecting, analyzing, and visualizing the relevant data. Like most things, it is a question of whether data and analytics are viewed as simply a nice feature or critical to growing and maintaining a business. Will and vision, not just resources, are crucial.
For those that are interested in the new frontier of data and analytics I would also recommend the following:
- AI and Social Science
- John Udell’s Blog
- Data Wrangling
- O’Reilly Radar
- FlowingData Beginner’s Guide
- Visual Complexity
If anyone has additional links or recommended reading feel free to leave it in the comments section or email me.