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Staffing in Big Data

Big data is the popular term used to describe both structured and unstructured data that is so big, and moves so fast that it’s difficult to process using traditional processing techniques. Big data can provide valuable information and can allow companies to instantly learn who did what, when they did it, and where it was done. Big data isn’t just a fad. It is something you need to be aware of if you want to stay competitive in the ever changing market. Big data can be leveraged to innovate and compete and has the potential to become the basis of growth for a company.

 Big data is changing the role of talent scouts.

You don’t need to be a data scientist to know there’s a skills gap. We already know we are experiencing a shortage of talent for the positions we need to fill today, now we are facing a problem filling positions tomorrow, especially when we are talking about the talent necessary to take advantage of big data’s business transforming potential. According to McKinsey Global Institute, by 2018 experts predict the United States will be facing a shortage of up to 190,000 people possessing deep analytical skills and a shortage of 1.5 million managers and analysts with the skills to use big data effectively.  Given the explosive growth on the help-wanted boards for data analytics experts and the intensifying competition to fill more jobs than there are qualified people, what can your company do to attract and retain talent?

Data is a Tool, but Staffing is the Focus

There are efforts afoot to overcome the big data staffing shortage. IBM has launched new big data curricula that they are spreading through universities to address the big data staffing shortage. IT professionals also will have to retrain to take on big data processing and analysis. But in the short term, IT managers will have to start seeking out data scientists, or grooming their own data scientists to support big data initiatives.

 Businesses anticipate a 131% increase in the need for analytics skills over the next 3 years

 The skills required for data scientists include strong data skills, analytical skills, knowledge of statistics, and the ability to program algorithms. Rather than trying to find all those stills in one professional, consider doling it out among big data staffers, or even promoting and training your own IT people. A big data analyst doesn’t have to have programming skills or build algorithms, although a strong background in SQL will help them understand the analytics involved. The analysts need to be able to interpret the data. Those are skills you can cultivate within your IT team. Or consider outsourcing to hire the necessary big data expertise.

As the marketing discipline has moved from promotion and print to algorithms and SEO, and hence hired to very different specs and searched for a new range of capabilities, so many other professions and industries will find themselves needing to change who they hire and how they find them.

Will we have the recruiters and hiring managers ready to find them?

Do our resources know where to look?

Are our assessment capabilities up to selecting the best skills?

Once you understand the basic requirements of big data analysis, you can assemble a strike force capable of handling any big data project. So how will you tackle your big data staffing needs? There are multiple ways; hiring, training, and outsourcing are a few of them.  It all depends on what caters best to the company’s needs and budget.

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