How Companies are Solving Big Data Skill Shortage


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From AI to autonomous cars to Internet of Things, Big Data has percolated every new technology, with companies investing heavily on Big Data Analytics. Since its birth in the late nineties, there has been a tremendous growth in Big Data-related technologies which have seen massive adoption across every global industry. However, the concept of Big Data has continued to remain unnoticed as far as general public is concerned.

 

Today, it’s the general public that’s driving the demand for big data solutions. It’s because of the unprecedented amount of data that people are generating everyday, through their laptops, phones and IoT devices. At this rate, by 2025, we’ll be generating 180 Zettabytes of data every year. To put things into perspective, it would require only 42 Zettabytes to store every spoken word by humans since the dawn of time.

 

Although it’s obvious that Big Data will continue to grow at a breakneck speed in years to come, the highly-skilled workforce required to fill Big Data jobs hasn’t materialized yet. As a result, businesses that adopt Big Data technologies have to compete to acquire the right talent that will help them derive valuable insights from their Big Data.

 

Here are some ways companies are overcoming this talent crunch

 

In-house training

Some of the most successful big data teams have been built by training from within the organization. This is because almost every business that adopts big data technology, has an in-house IT team.

 

Also, some of the big data technologies such as Hadoop aren’t difficult to learn for IT staff that’s already familiar with many of the big data concepts. However, the surge in demand for big data professionals has given rise to a whole new industry that helps businesses train employees. For example, companies like Cloudera provide a wide range of big data training options to any organization that needs it.

 

Leave it to the Experts

Just as with other erudite technologies, many companies are turning to third-party consultants, vendors and experts to help them with their big data requirements. This is the most straight-forward solution for firms whose core area is not technology. Instead of spending a fortune on hiring specialists that they may be unable to properly manage, organizations are relying on reputed consulting firms like Accenture, IBM, Dell to help them setup and manage the required big data technologies. It makes sense, considering the fact that companies like IBM, Dell, and Microsoft are already building many of the underlying technologies and, therefore, have people who are experts in the field.

 

Turning to Specialized Portals

Big Data has certainly caught the attention of the hiring and recruitment industry, and there are already some big data-specific hiring sites. Since the talent pool is quite small compared to the size of the industry, it’s a close-knit community. Apart from specialized job boards and portals, companies are also dipping into online communities like Kaggle, where data analytics and professionals from all over the world gather to collaborate, solve data problems and share experiences. Such sites provide a great way to connect with people who have the specific skills required to execute big data projects.

 

Thinking about the Future

Most companies that are adopting big data, know that they’re facing an evolving industry that will require regular staffing and technological adjustments. That’s why it’s common to find many organizations using a combination of the above approaches at the same time. This way businesses can embrace big data trends of the present without compromising the flexibility for the future.

 

For example, some companies are training their staff about emerging big data technologies, with an eye on the future, while outsourcing existing projects to third-party consultants and experts. While working with big data, it’s essential to remember that there’s no best way to do it, and you might even need to build custom solutions depending on the situation. Until the educational institutions produce a generation of data scientists and engineers, it’s the hybrid approach that will save the day.

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