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Data science VS Business Intelligence (BI)

Many have come to view data science as new business intelligence. However, data science and business intelligence are actually two very different disciplines, and one cannot replace the other. In fact, both data scientists and business analysts work together in different but related roles in big data, turning raw data into useful and actionable information.

Further, both data science and business intelligence allow organizations to uncover the information within raw data that may be commercially or socially useful. Many organizations require the expertise of both data scientists and business analysts to optimize their use of big data.

Business Intelligence

The business intelligence process includes providing retrospective reports to help businesses monitor the current state of their business and answer questions about historical business performance. In other words, business intelligence focuses on interpreting past data. Business analysts perform meticulous, plan-based work that includes assembling pieces of the big data puzzle to arrive at concrete answers.

Business intelligence tends to focus on reporting, dashboards, and alerts, all of which have the value of visualization. Easily digestible deliverables—pie charts, bar graphs, and the like—serve as the hallmark of business intelligence. The value of business intelligence lies in its accessibility. Although organizations use business intelligence in strategic decision making, it does have its limitations. Most importantly, business intelligence tools work with variables that already exist. In other words, we have to know what we are looking for to use business intelligence tools.

Data Science

Data science differs from business intelligence in that it makes use of past data to make future predictions. Many times, data scientists help companies mitigate the uncertainty of the future by making predictions of future performance.

While business intelligence tends to be structured, data science leans more toward the unstructured. In other words, data science deals with incomplete, messy, unorganized data, not immediately usable without some degree of cleaning and prepping.

Data science and business intelligence exist on the same spectrum, albeit at opposite ends. Business intelligence focuses on managing and reporting existing business data in order to monitor areas of concern or interest, while data science generates predictive insights and new product innovations by applying advanced analytical tools and algorithms.

The data science toolkit is more technically sophisticated than the business intelligence toolkit, with data scientists utilizing tools such as advanced statistical packages, SQL, Hadoop, and open source tools like Python and Perl.