Data Science-1.pdf - Data Science vs Business Intelligence What's the Difference Data scientists and Business Intelligence(BI analysts have different

Data Science-1.pdf - Data Science vs Business Intelligence...

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Data Science vs. Business Intelligence: What's the Difference? Data scientists and Business Intelligence (BI) analysts have different roles within an organization; usually, a company needs both types of professionals to really optimize its use of data. In a nutshell, BI analysts focus on interpreting past data, while data scientists extrapolate on past data to make predictions for the future. Data Scientists and Business Intelligence Analysts Are in Demand Data scientists and Business Intelligence (BI) analysts have different roles within an organization; usually, a company needs both types of professionals to really optimize its use of data. In a nutshell, BI analysts focus on interpreting past data, while data scientists extrapolate on past data to make predictions for the future. Data scientists help companies mitigate the uncertainty of the future by giving them valuable information about projected sales and making general predictions of future performance. BI analysts, on the other hand, interpret past trends. These big data professionals perform more meticulous, plan-based work; they slowly put together the pieces of the data puzzle to arrive at concrete truths, rather than making guesses based on probability. Both types of professionals are necessary to maintain a company’s financial health. Data Scientists and Business Intelligence Analysts Are in Demand Data scientists and BI analysts share great job prospects, since companies are struggling to fill positions in these fields. According to the McKinsey Global Institute, the U.S. currently labors under a shortage of 140,000 to 190,000 professionals with specific analytical expertise. A Burtch Works survey said that 89 percent of data scientists on LinkedIn were contacted about job opportunities monthly, and 25 percent received weekly job offers through the site. The situation is expected to become far more serious over the next few years. By 2018, the McKinsey Global Institute predicts that U.S. industries will add four million more big data positions, and those positions will all need to be filled with professions who possess quantitative and analytical skills. By that year, the country can expect a shortfall of 1.5 million analysts and managers who can analyze big data and make sound business decisions based on that analysis. What does it take to build a career in big data? In addition to an advanced degree in mathematics, statistics, computer science, engineering, or business intelligence, desirable job candidates must have good business sense and strong communication skills. Big data job prospects are already great even if you’re a new graduate just entering the field, but once you have a few years of experience under your belt, you can expect your job prospects to increase exponentially.
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  • Fall '17
  • taimoor
  • Data Scientist

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