Learn How to Bridge the Big Data Skill Gap in 2018


In the next few years, big data technology will continue to remain the ‘Big thing’ for large enterprises. Tech experts have estimated that the amount of data large enterprises produce every day could be worth trillions of dollars or even more. Access to such a huge amount of data can be a blessing or a curse for businesses. If churned well, it is not only helpful in deciphering information, but also in reducing decision-making times. On the other hand, access to large and widely disparate sets of data increases the need to hire big data analysts to draw meaningful business insights from the data. To exploit big data, business organizations will have to mend the big data skill gap. Listed below are some of the best ways to bridge the big data skill gap in 2018.

#1 Scout for the right resources with the right skill set

A good big data scientist should have an analytical mind along with a strong background in statistics and mathematics, particularly, linear algebra and calculus. One must be able to handle large sets of data, crunch numbers, understand the concepts behind data modeling, and derive meaningful insights from the data. Apart from this, data scientists should also have sound knowledge of the business domain and good understanding of business processes and customers.

#2 Training the current resources with the right skill set

It is generally seen that many companies use a combination of upskilling, hiring, and outsourcing to bridge the demand-supply gap. But, as we all know, interviewing and on boarding candidates, working with recruiters, and getting new positions approved is a time-consuming process. Instead of hiring new data scientists, companies should upskill their existing resources to bridge the big data skill gap in the company. Once you organize corporate programs in big data and provide training to your existing resources, they will be able to analyze large, messy, unstructured data quickly and draw meaningful insights from the data. Always remember that big data is creating big value calls for retraining and reskilling existing resources so that that they can make data-driven decisions. Many organizations that are leading the big data revolution already have a numerate, experiment-focused, and data-literate workforce.

#3 Outsource big data needs if you are a small company

We all know that meaningful information can be derived from big data, but accessing such a huge amount of data is not child’s play. Many small and mid-sized enterprises are collaborating with third parties to create and implement big data analytics strategies. Partnering up with a big data team seems like the best way for small and mid-sized companies to stay ahead of the game.
If you also know some good ways to bridge the big data skill gap in 2018, let us know in the comment section below.

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