{"id":6651,"date":"2019-08-26T11:15:28","date_gmt":"2019-08-26T15:15:28","guid":{"rendered":"https:\/\/blog.brainstation.io\/?p=6651"},"modified":"2020-12-14T10:35:07","modified_gmt":"2020-12-14T15:35:07","slug":"what-is-data-science","status":"publish","type":"post","link":"https:\/\/brainstation.io\/blog\/what-is-data-science","title":{"rendered":"What is Data Science?"},"content":{"rendered":"

In 2009, Google\u2019s Chief Economist, Hal Varian, told the<\/span> McKinsey Quarterly<\/span><\/i> that \u201cthe sexy job in the next ten years will be statisticians.\u201d As crazy as it might seem to use the words \u201csexy\u201d and \u201cstatisticians\u201d in the same sentence, he was right. <\/span><\/p>\n

Nearly ten years later, we’re inundated by data. In fact, <\/span>every day, 2.5 quintillion bytes of data are created<\/span><\/a>. <\/span>If this avalanche of numbers has accomplished anything, it\u2019s in making the benefits of data analysis abundantly clear. According to <\/span>researchers from MIT<\/span>, \u201ccompanies in the top third of their industry in the use of data-driven decision making were, on average, 5 percent more productive and 6 percent more profitable than their competitors.\u201d<\/span><\/p>\n

It\u2019s no surprise, then, that data science jobs are some of the fastest-growing, most in-demand in technology. Since 2012, <\/span>Data Scientist roles have increased by 650 percent, <\/span>and this rise shows no sign of stopping. In the next two years alone, the number of available data jobs in the US will increase by 364,000 to 2.7 million. In response to this influx, data courses such as BrainStation’s full-time Data Science Diploma program<\/a> are on the rise to help fill the rise in job openings. <\/span><\/p>\n

But the question remains…<\/span><\/p>\n

What is Data Science? <\/span><\/h2>\n

Data science makes use of predictive causal analytics, prescriptive analytics, and machine learning<\/a> to help us make predictions, and more importantly, decisions. <\/span><\/p>\n

Let\u2019s put it in simpler terms: data science uses math and technology to find hidden patterns (and ways to be more productive and profitable) in raw data. To find those patterns, a Data Scientist spends a lot of time collecting, cleaning, modeling, and examining data, from numerous angles (some of which have not been looked at before). <\/span>
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\nThis exhaustive approach is one of the reasons why, as Biostatistics Professor <\/span>Jeff Leek once wrote<\/span>, \u201cthe key word in data science is not data; it is science.\u201d <\/span><\/p>\n

To find hidden patterns, a Data Scientist<\/a> uses a combination of techniques and concepts, including: <\/span><\/p>\n