With technical skills such as Java, C++, Python and more in high demand for “Big Data” analytics, it seems like softer business skills such as speaking, writing, planning, leadership, negotiation etc. are falling by the wayside.
With technical skills such as Java, C++, Python and more in high demand for “Big Data” analytics, it seems like softer business skills such as speaking, writing, planning, leadership, negotiation etc. are falling by the wayside. But the ability to communicate, relate and navigate throughout an organization—so called “softer skills”—are especially needed to propagate analysis and communicate the impact of data-driven decision-making.
In 2012, cloud computing blogger David Linthicum penned a short piece explaining “3 Winners and 3 Losers in the Move to Big Data”. In the post Linthicum identified one “loser” as data warehouse and BI specialists, presumably because these folks were accustomed to using languages like old-school SQL and supporting “legacy BI” systems.
It’s interesting that as we find ourselves nearing mid-2013, those “legacy” skills of writing for and supporting various BI tools and relational databases are not going away. In fact, the opposite seems true as open source programmers seek more ways to make projects SQL-like to access various distributed file systems, NoSQL and NewSQL data stores. And while the development of SQL-like interfaces helps the business analyst utilize some of these newer platforms, business skills seem to get short-shrift in the equation of making an analytics program a success.
It appears the burgeoning role of “data scientist” intends to bridge the gap between technical skills and business acumen. An IBM blog states that while the formal training of a data scientist should include an understanding of computer science, applications and ability to write in various languages, they also need to have business smarts. Thus the data scientist role must marry technical skills with “the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge.”
It would seem that bridging the technical and business acumen gap with the data scientist role is an excellent idea. However as many articles on this site point out, data scientists are in high demand and can cost an organization a pretty penny. And at this point, there just aren’t that many data scientists available on job boards, or willing to move out of Silicon Valley. So it appears that while there are plenty of employees with technical skills, and line of business leaders that understand the inner workings of the enterprise, there’s still a gap that needs bridging. What’s a company to do?
While it’s debatable whether a business analyst can be taught the necessary technical skills to become a data scientist, we can definitely ensure that we don’t neglect softer business skills in the evolution towards a data-driven organization. For example, there are universities that offer classes and executive course work on negotiation, communication and selling skills. In addition, there are programs available such as Toastmasters that can teach leadership and public speaking skills.
Need help writing? Your local university likely has coursework and workshops to improve business writing for proposals, sales briefs, whitepapers and more. Finally, there are too few employees that can perform “critical thinking”, or the ability to conceptualize, analyze and then evaluate various streams of information. Coursework from universities across the globe can also assist in this area.
What say you? Are better business skills needed for analytics professionals? If so, what are those skills? Finally, how would you recommend developing an action plan to “perform a business skills upgrade”?
(image: business skillset / shutterstock)