Key Data Skills for 2018

Data is the gasoline that drives the engine of today’s businesses. Being able to work with data competently and capably is an advantage now, but it will soon be an imperative. That’s why companies are ferociously recruiting for big data jobs. According to McKinsey, there will be a shortage of 190,000 data professionals by the end of 2018.

Just because data skills are in high demand, however, does not mean everyone is the ideal candidate. It’s not worth it for companies to fill a crucial role with an incomplete, incapable, or incompetent candidate. They are looking for recruits with the skills that are most relevant to today, and the flexibility to pick up the skills necessary for tomorrow.

Maybe you are considering a career as a data analyst. Maybe you are searching for work as a data analyst. Or maybe you are trying to recruit the best data analyst on the job market. In any case, consider these data skills to be key for 2018 and beyond:

Apache Hadoop

Hadoop is one of the preeminent big data platforms. And even though it has been around for over a decade, it continues to be widely utilized and evolved. A new version of Hadoop was released in late 2017, and demand for development continues to be brisk. But as functional as the platform is, it is also notorious for being vulnerable to confusing and complex issues. Companies will be actively recruiting Hadoop experts throughout 2018 and likely for many years to come. Experts in big-data components present within the Hadoop stack – Pig, Hive, HBase etc. – will be the most in-demand.

NoSQL Database

Next to Hadoop this is probably the leading data technology. These databases handle unstructured data, which is expected to form the lion’s share of all data collected and stored over the coming decade. The demand for NoSQL professionals is robust throughout industries (along with the compensation), but healthcare is recruiting especially actively.

Apache Spark

Companies love this data tool because it enables incredibly fast processing and makes analysis almost instantaneous. The companies that are leveraging data-driven analytics to gain an advantage over competitors know that speed is key. The technology is open source, making it easier for inexperienced professionals to access informal learning and training. Demand for qualified professionals is especially high since there are so few Apache Spark professionals available on the current labor market.

Artificial Intelligence in Data Analytics

Though companies have used data-driven analytics to guide their decision-making for years, the future of this industry is artificial intelligence. This means there is a demand for specialized skills in this area. It’s no wonder that machine-learning engineers are projected to be some of the most in-demand jobs over the next five years. Professionals with the requisite AI-based skills and especially with relevant experience can expect to be actively recruited by Fortune 500 employers.

If you are a data analyst or technician this list should be cause for excitement. You likely have some understanding of these skills/technologies already, and you are uniquely able to learn new data skills. The future looks incredibly bright in terms of opportunity, compensation, and stability.

For recruiters, the situation is a lot less exciting. Demand for data skills is huge, but the supply is limited and not likely to grow fast. Most companies realize they need to get better with data, but they must fight to attract candidates and pay handsomely to retain them.

The solution is to look at the other direction of big-data – the development of intuitive tools. These are a lot more accessible and affordable over the long run. Plus, with the right tool the full potential of big data is unleashed. Adding to your teams is not unimportant but adding to your tech is equally important.