by Angela Guess
Rick Sherman recently commented on the impending shortage of Big Data professionals. Sherman writes, “The gap we are going to encounter in this industry is the shortage of both the skilled people to develop the Big Data analytics models, often referred to as data scientists, and the data-savvy business people to take advantage of them in their business. The McKinsey report states ‘By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.’ Our industry has faced a shortage of skilled people in business intelligence, analytics and data integration that has kept business from effectively using the data they already have. With the onslaught of Big Data and the advanced skills it requires, we’re destined to fall even further behind.”
Sherman adds, “If we are ever to fill that gap we need to broaden our definition of what a data scientist is. This title and the job descriptions that are posted for these jobs are too concentrated on programming and IT skills. In order to create Big Data analytical and predictive models the person does need to have programming skills, but more importantly, that person needs to understand statistical modeling. To develop the model, the person also needs to understand their business and industry. It also helps if they understand how to apply customer behavior and economic models. Although Big Data means ‘a lot of data,’ the reality is, in many cases, that data is incomplete and inconsistent. Developing analytical models means dealing with dirty data and gaps. Many ‘numbers’ people have trouble dealing with these conditions.”
photo credit: dreamcicle19772006
