Uncertainty Drives Desire to Improve Big Data Skills

Uncertainty Drives Desire to Improve Big Data Skills

Uncertainty Drives Desire to Improve Big Data Skills
Thousands of data science professionals descended on the San Jose Convention Center, in the heart of Silicon Valley, in late March to learn about the high-demand skills of the future. Some were at the STRATA convention to network; others were there to learn new skills to further their careers in data science. But even with data science being dubbed “the sexiest job of the 21 century,” many attendees shared an uneasy feeling of uncertainty about the future of this fast-moving field.

Northeastern University-Silicon Valley conducted a survey at STRATA, the largest annual gathering of statisticians. The results showed that a huge majority of those in attendance (96 percent) thought that acquiring new skills in data analytics would help them with career opportunities and growth. Even more interesting was the fact that more than two-thirds of that group (68 percent) was already employed in the data science field. In other words, many people already working this field don’t feel they are aptly prepared. Nearly two-thirds of respondents (63 percent) ranked data science-advanced analytics as their most coveted skill to learn. The rapidly evolving progression of the field, in combination with the massive amounts of data, explains this concern among professionals in the industry.

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Today’s data scientists differ from their counterparts of just a few years ago. In the past, data scientists had to do it all. They had to be proficient in everything from complex back-end calculations to extracting data, analyzing it, visualizing it and, ultimately, presenting it. I liken the change we are seeing in the field now to that in the field of medicine. As the field swells, it’s getting to a critical-mass situation and subdividing into specialization.

Of course, each candidate must still have the skills in math, business technology, behavioral science, and design thinking. But the requirements don’t stop there. The data is demanding more and as the profession matures, and the expertise of the workers must evolve to meet these demands. The volume of data to be analyzed keeps increasing, making it more challenging to keep up with the skills needed to sort through all the information. This creates a near constant need for upskilling.

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It’s not just important to have the skills to manage all that data. Once you have extracted what is crucial from the data, you have to be able to decide what to do with that information. Survey respondents believe that top employers see data management and data analysis traits as key to getting the job. Additionally, respondents felt their skills were lacking in the areas of advanced analytics, data mining, Hadoop, and statistical computing.

Respondents’ preferred method of learning was also a key component of the findings. Just as the skillsets are multifaceted, so is the approach to building them. For many of these professionals, returning to school full-time simply is not an option.

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