Often the terms business intelligence and data analytics are used interchangeably in common dialogue. Both terms share many similarities, however, the types of analytics they create are categorized as fundamentally different. There are situations when each has their merits, but business intelligence is typically easier to implement for an organization and is currently more adopted in business practices.
Both methods are about turning data into more meaningful and useful forms. Businesses can use each method to achieve better results across the business even though they are used in different ways. Cleaner data provides better results within each method as well. While they both give more meaning and can lead to great results, they have some fundamental differences that make them useful for different situations.
Business intelligence is comprised of descriptive information that provides support for decision-making activities (Covington 2016, 153). It is information that helps someone understand what is happening and enables them to make better decisions from that understanding. Business intelligence tools use historic data stored in data warehouses to accomplish this. The reports use simpler mathematics typically and are focused on analyzing historic data in ways that inform past performance.
Data analytics on the other hand takes raw data and turns it into a meaningful format that is predictive and prescriptive to make predictions and forecasts (EDUCBA 2020). Data analytics takes that raw data and models and transforms the data. Transforming the data involves finding connections within the data using complex mathematics and statistics. This helps managers to understand what actions to take and new opportunities to explore.
While both methods lead a manager to better decision making, data analytics can help managers predict and understand potential new outcomes. Instead of figuring out what happened, it tries to figure out why. This requires deep mathematical expertise and programming, as well as a clean data set. Business intelligence allows a person to understand historical performance and answer questions about what happened to inform future decision making. Since business intelligence just requires historic data and some simple statistics, it is much easier to develop and begin using. Business intelligence tools are a great starting place for an organization and can lead to further predictive and prescriptive data analytics as an organization matures in its data culture.
Author: Logan Callen
EDUCBA. 2020. “Business Intelligence vs Data analytics.” EDUCBA.com, February 04, 2020. https://www.educba.com/business-intelligence-vs-data-analytics/
Covington, Daniel. 2016. Analytics: Data Science, Data Analysis and Predictive Analytics for Business. 5th Edition. South Carolina: CreateSpace.