To those of us who do not work closely with data science, like those on the management side, business intelligence (BI) and business analytics (BA) might not create the image of two distinct domains but perhaps of two overlapping circles. Although in some sense the image of overlapping circles is not entirely wrong, there are many inherent characteristics which differentiate the two. Business owners should be aware of these so that they can employ them in their best capacities.
The basic difference
BA is an umbrella term that comprises skills, applications, technologies, and practices meant to interact with available data, discover patterns and insights, and follow through with the appropriate action. BI, on the other hand, is an area that comes under analytics and which focuses on measuring past data and gleaning information to enable structured business planning. Intelligence can be used to answer questions like “what happened,” “how it happened,” and “how often it happened.” Analytics can tell you “what will happen if this policy is changed,” “what do we need to do next,” and so on. To be very concise, analytics looks at the future and intelligence looks at the past.
Difference in methodology
Advanced analytics includes technology for data, text and multimedia mining; descriptive, predictive, and prescriptive modeling; statistical or quantitative analysis; simulation; and optimization. BI makes use of reporting tools (KPIs, metrics), scorecards, dashboards, automated monitoring, OLAP, and ad hoc query. The kind of knowledge generation in analytics is automatic, and manual in intelligence. Despite the differences in outputs and methodologies, both are used to work on big data.
The core group of an organization that is responsible for mitigating risks and taking the company forward uses analytics to deal with unanticipated outcomes and optimize possibilities. BI is limited to generating and distributing automated reports on pre-determined metrics and assumptions. BI can use Excel to show answers for a query by fetching appropriate information from the pool of data; however, it cannot help managers and policy makers to come up with responses to new events. Moreover, the insights that a person can glean from looking at the Excel sheet will remain with them, as it cannot be utilized for organizational learning or improving processes.
Both domains offer different career paths for a student. Courses in analytics will lead them to be analysts (no prizes for guessing!), data scientists and similar professionals while someone trained in BI technologies can bag the roles of administrator, consultant, or manger. Knowing the differences between both domains enables students and budding professionals to make the right career choices and helps business users to buy the correct technologies and skills for their intended results.
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