How Companies are Meeting the Big Data Skills Challenge

Corporate culture is evolving to compete in the arena of Big Data. Outside consultants are in high-demand as the talent pool is still small. 

December 15, 2017
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Big Data is everywhere. From the birth of the concept in the mid-1990’s to today, there’s been staggering growth in related technologies and adoption rates across every global industry. The trend has been enormous, and yet, the concept of big data managed to fly mostly under the radar as far as the general public was concerned. 

It’s the general public, though, that’s driving much of the demand for big data solutions. That’s due to the unprecedented amounts of data that people generate using their computers, smartphones, and IoT devices on a daily basis. Current estimates indicate that 180 Zettabytes of data will be created globally each year by 2025. 

To put that number into perspective, consider that it would only require about 42 Zettabytes to store recordings of every word spoken aloud by humans since the dawn of time. 

It’s clear from the statistics that big data will continue to grow exponentially in the years to come, but so far, the workforce that’s needed to fill the associated high-skill jobs hasn’t yet materialized. For businesses adopting big data technologies, the race is on to acquire the talent needed to thrive in the modern economy. Here are some of the ways they’re doing it. 

Training From Within 

Some of the most successful big data teams to date have been grown from within existing organizations. This is thanks to the fact that almost every existing organization has some IT staff with which to work. 

In addition, many big data platforms, like Hadoop, aren’t that difficult to learn for technology staff that are already used to many of the key concepts. The overall demand for these skills has also created a whole new learning industry, which can help businesses to train up employees. Companies like Cloudera have a range of options that bring big data training to any organization that requires it. 

Leaving it to Experts 

As with many other specialties in technology, many companies are turning to consultants and third-party vendors to satisfy their big data needs. This is an especially attractive option for firms whose core competencies don’t lie within technical fields. Rather than spending large sums of money to hire specialists that they lack the knowledge to properly manage, many are leaving the task to consulting firms. This makes sense, given that tech giants like IBM, Dell, and Microsoft are building some of the underlying technologies and therefore already have staff that are leading experts in the field. 

Turning to Specialized Portals 

The rise of big data hasn’t gone unnoticed in the recruiting and staffing industry, and there are already some thriving big-data specific hiring sites. Since the available talent pool is still small when compared to the sheer size of the big data industry, it’s become a tight-knit community. Aside from specialized job boards, there are also online gathering places like Kaggle where analytics and data engineering professionals around the world gather to collaborate and share experiences. These types of sites provide an excellent way to connect with people that have the exact skill set required for any number of big data projects. 

Building for the Future 

Most companies that are pursuing big data solutions know that they face an ever-evolving industry that will require constant staffing and technological adjustment. That’s why it’s quite common to find that a combination of these approaches is in use simultaneously. In this way, businesses in the digital age can embrace the big data trends of today without sacrificing their flexibility for the future. 

For example, some companies are training existing staff in emerging technology while farming out current workloads to third-parties and consultants. What’s certain is that much like in big data itself, there’s no one correct way to do it, and solutions may be custom built depending on the situation. Until the educational sector begins to produce a new wave of data scientists and engineers, it’s the hybrid approach that will continue to win the day.