Data is everywhere, to the point that we’re practically swimming in it, if not drowning. But are we putting it to good use?
We’ve had data in one form or another since the beginning of time, but in 2017, we have more than we know what to do with. As technology has evolved, so have the ways to gather data and therefore the amount, so that data collection now grows exponentially. IBM reports that 90 percent of the data we have was collected in just two years, as we produce and gather it at a rate of 2.5 quintillion bytes of data a day. And that report is from December 2016, so imagine how much more we’ve collected since then?
Obviously, generating and collecting data is not the issue. We’ve mastered that. However, there’s a catch: All of that data only has the potential to be useful. Simply collecting data is not enough. It must be stored, accessed, managed, analyzed and utilized. Otherwise, it has no value—at all. And it takes people with the right training to make all of that happen.
Businesses the world over are attempting to make use of the data they have, and they will only grow more data-driven over time. But do they have the employees to make that happen? Not necessarily.
Data Drives Business Today
There’s really no reason not to be putting data to use, and companies know it.
As just one example of an organization putting data to use in a significant way, industry expert Ronald Van Loon describes how Airbus is using Big Data to save millions of dollars per year. Airbus, a global leader in the aerospace industry, has tapped into data to be more efficient, productive and innovative. For example, the many terabytes of data generated by their airplanes are now used to inform predictive and timely maintenance programs that keep airplanes flying—and customers happy.
In another use case, Walmart has learned to use Big Data to get extremely granular and targeted, and drive supermarket performance. Analysts have used data to learn that people in some areas buy more strawberry Pop Tarts when preparing for emergencies, to discover in real time that cookies weren’t selling on Halloween because merchandisers forgot to display them and to realize a drop in product sales was due to a pricing error. In the first case, extra Pop Tarts were stocked (and sold). In the case of the cookies, the problem was rectified within hours. And in the third, once the problem was spotted, it was fixed right away. It used to take two to three weeks to identify a problem. Now it takes 20 minutes, using data and analytics.
Big Data Jobs Outnumber Big Data Professionals
The use cases are there. The value of data has been proven time and time again. The problem is, the number of people qualified for Big Data jobs has not kept pace with the explosive growth of the data itself.
According to an article on this skills gap published at Forbes, the annual demand for data scientists, developers and engineers will reach nearly 700,000 openings by 2020.
McKinsey & Co. predicts that by 2018, data science jobs in the U.S. will exceed 490,000 but there will fewer than 200,000 available data scientists to fill those positions.
On a broader scale, research by MGI and McKinsey’s Business Technology Office predict that by 2018, “the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.”
The bottom line is, businesses could benefit more from their data with the right staff, and at the rate we’re going, they won’t. Hence, the need for more training in data analytics, database management, and other related big data skill sets.
Close the Data Skills Gap by Training the Employees You Already Have
Where will you find your future data scientist, data engineer, data analyst and data developer candidates to fill those Big Data jobs? Will you have to get into recruiting wars to snag some of these in-demand professionals? You don’t have to. You can simply get your own IT staff trained for these new roles. That guarantees you have the skillsets you need in-house already.
There are also significant financial reasons for choosing to train existing employees rather than hire new ones.
- Employees are more likely to stay with a company when they have training opportunities and that helps you with retention
- Retaining employees keep your social capital intact which prevents disruptions in the workplace and therefore saves money
- And then there are the costs associated with hiring and onboarding a new employee, costs that can reach as high as 200 percent of their annual salary
What do your employees need to learn how to do to tackle Big Data? According to datanami, the top skills needed for a move into Big Data are mentioned below, although the needs at your organization will determine which specific skills are needed.
Admittedly, that last one can be a challenge to teach, but you already know who among your IT employees has the potential to bring creativity and problem-solving skills into a new role in data. Tap those people for training for sure.
The training that will make your employees Big Data ready is easy to find and to get. Companies like Simplilearn offers a Data Scientist Master’s Program as well as courses in a range of data topics, like Hadoop, Tableau, data visualization, business analytics, MongoDB and many more. See a comprehensive list of courses in Big Data and analytics here.
However, how you choose to go about getting your employees trained for the data-driven economy that is now upon us matters less than getting started. We already have a skills gap and a shortage of qualified people for the growing number of jobs. In order to truly take advantage of the benefits that Big Data will bring to your business, be proactive and get your people ready today so you can put that data to use tomorrow—gaining a competitive advantage over those businesses that choose to chase a dwindling supply of candidates instead.