While college students have long been encouraged to learn coding, employers are increasingly seeking candidates with broader data analytics skills, one expert argues.
Experts Exchange COO Gene Richardson notes that a number of initiatives, such as President Obama's TechHire Initiative and Computer Science for All program, focus on hard coding skills. However, most businesses in the United States need employees whose technical knowledge goes beyond coding alone.
Instead of just teaching students C++ or Java, Richardson says, colleges should be helping them develop other technical skills, including:
Scripting language basics
Simple SQL commands
Understanding the SQL programming language allows users to process and make sense of raw data.
"Sure, the right people on your team should know how to code—but most of them should be writing spreadsheet macros and pivot tables to support your internal business processes, not agile algorithms for entrepreneurial [endeavors]," Richardson says.
Simply collecting disparate pieces of data isn't enough; employees must be able to draw conclusions from that raw data.
Richardson discusses a time when a statistics expert was brought in to present findings on Experts Exchange's website traffic patterns. The expert could not explain the context or meaning behind the raw data that he had collected. According to Richardson, the expert's basic computational skills could not make up for his lack of analytical skills.
"Nowadays, the most in-demand coding skill in the world is not the one that empowers you to build a startup that boosts national GDP, it's the ability to perform advanced analysis on data that creates rich meaning from raw numbers," Richardson says.
Converting numbers into action
The situation at many companies is best summarized in the phrase "I'm drowning in data but starved of insight," says Keith O'Brien, practice manager at EAB. He explains that organizations have more data and more platforms for collecting it, but lack two critical pieces for turning that data into action.
First, many data scientists are unable to translate their findings into actionable recommendations for managers. In this case, being a T-shaped professional can give data scientists an advantage.
"Boot camps are fine—but for those looking to leverage an analytical proficiency to advance their careers, they need the business acumen and soft skills too," O'Brien says.
The second missing piece is on the manager side: many individuals still don't have a strong grasp on how data is generated and the best ways to use it. Training in data and analytics can be very helpful for decision-makers, according to O'Brien, because it helps them work with data scientists more confidently and understand where analytics can add value to their business decisions. Data skills complement the intuition and experience that managers bring to decision-making.
"Looking at the T-shaped professional again, you could envision in the next 5 to 10 years that a working understanding of analytics becomes a part of the top bar because it works across roles and lines of business," O'Brien says (Taylor, HR Dive, 7/26; Richardson, VentureBeat, 7/17).
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