Companies all over the globe are embracing the big data revolution at a staggering pace. The latest data indicates that 53% of companies had adopted big data platforms by the end of 2017. That figure represents a 36% increase over a span of just two years. That giant leap has produced something of a talent gap in the modern workforce, with the need for data science skills far outpacing the supply of trained workers.
A lack of candidates with skills in data science was already apparent in 2015 before the adoption rate had even swelled to where it stands today. To meet the demand, companies have increasingly turned to hiring from within and skills training initiatives as stopgap measures. As it turns out, those methods may be the most effective way for businesses to acquire the exact skills they require, and existing employees hold the advantage of industry familiarity and intimate knowledge of their specific business. Here are three ways that companies can train up existing employees to meet their big data skills demand.
Big Data Boot Camps
For businesses that already have staff with programming knowledge, there are a variety of big data boot camps available to teach them vital data science skills. A boot camp refers to a short, focused intensive training program that is designed to enhance an employee’s skills in data science by building on their existing knowledge in programming or computer science related fields. Due to the current level of demand for data science skills, there are already a variety of boot camp programs available. Some offer broad, generalized training, such as those offered by industry leader Metis. Others are specifically tailored to individual industries such as healthcare, like the Insight Health Data Fellows Program.
Another common avenue of training is the creation of an employer-sponsored degree program for qualified employees. This method is particularly useful for companies that have existing employees that already hold bachelor’s degrees in computer science, mathematics, or statistics. In those cases, companies may choose to sponsor part-time education programs for employees to earn a master’s degree in data science. Such degrees are the most common level of educational attainment for today’s data science professionals, representing 64% of the data science workforce in 2017. There is a wide variety of master of data science programs available online, such as the one offered by James Cook University.
There are some situations where a business needs to train employees for one specific big data platform or application. This is common for businesses that opt to outsource the majority of their data operations but lack the internal talent to make full use of the customer-facing components provided to them. Certification programs are available for a variety of applications, ranging from data visualization tools to programming languages like python. Online learning platforms like Coursera and Udemy provide customized instruction for just about any data science topic imaginable and allow existing employees to gain new skills at their own pace.
Staying Ahead of the Curve
By employing a mixture of these methods to allow existing staff to meet growing business demands for data science skills, companies can ensure a steady, reliable flow of qualified big data professionals within their ranks. They are also an excellent way to increase employee retention. In fact, 76% of the current generation of employees view professional development opportunities as an important part of company culture.
In a competitive field like data sciences, that’s a retention benefit that no business can afford to ignore. As big data solutions continue to permeate industries all over the world, creating effective ways to meet the demand for data science skills is fast becoming the business challenge of the 21st century, and for companies looking to meet that challenge, it should be comforting to know that there are plenty of accessible ways for them to do so.
The post 3 ways to close the big data skills gap from within appeared first on Big Data Made Simple – One source. Many perspectives..