The Biggest Misconception Between Business Intelligence and Data Science

By Alex Carbor · Originally published on LinkedIn, December 2017

Business intelligence and data science are often confused, especially by those unfamiliar with the industry. They are not synonymous, however. Business intelligence involves data, yes, but it's more about the operational and contextual aspects of your organization. Through this process, you answer questions such as what, when, how or who. Learning more about your customers and audience, for example, is one aspect of business intelligence.

On the other hand, data science has more to do with predictive analytics. The goal is to collect enough information you can use to build discernible patterns and insights. For example, data science can help you understand why something happened, or when it will happen again. Additionally, data science can answer what will happen if you change various aspects of a process or business plan.

For this reason, data science is more about data mining and statistical or quantitative analysis. It's also useful for predictive modeling, multivariate testing and process planning. To wrap this point up, don't get the two concepts confused.

Source: insidebigdata.com, "5 Misconceptions About Data Science" (Dec 28, 2017)

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