The terms “Business Intelligence” and “Data Analytics” are often used interchangeably, but they are in fact two separate processes that serve different purposes. The truth is you cannot successfully implement one without the other, and for those who are serious about using data to derive actionable insights, it’s important to understand the difference between the two.
What is Business Intelligence?
Business Intelligence (BI) focuses on using historical and real-time data to achieve operational efficiency. It is a process that uses aggregation, analysis, and visualization to uncover trends and aid in decision-making. It is particularly useful to executives and managers, as most BI tools are designed to display data in a way that is easily digestible and doesn’t require assistance from IT. It is primarily applied to run reports and enhance operational abilities. Business Intelligence shows you what has happened and how it happened, allowing you to map the changes and trends that led to the present moment. Some popular Business Intelligence tools include Domo, Tableau, and Microsoft Power BI.
What is Data Analytics?
Data Analytics is a science that uses predictive algorithms to forecast future business trends. It analyzes data to uncover why things happened and uses those insights to make predictions and show a more complete story. It uncovers relationships and causality in your data sets through the use of data mining, predictive analytics, and statistical analysis. This fuller picture of where your business has been and where it’s going drives innovation and operational success. Some of the above-mentioned BI tools now have an analytics feature added, but many companies rely on the analytic powers of products such as Sisense, Looker, and Zoho reports.
Business Intelligence and Data Analytics Work Together
To better understand how Business Intelligence and Data Analytics work together, let’s pretend you’re coaching a basketball team and you’d like to review your most recent game. Business Intelligence would show you all of the statistics relating to your team and players, i.e. you had possession of the ball for longer than your opponents, and you scored more points in the first half. Data Analytics would then dive deeper to provide more detail: were your players tired in the second half? Which ones consistently performed well throughout? What can you do to increase the efficiency of all players in the next game? These questions allow you to replicate success and avoid future failures.
BI and Data Analytics Aid in Decision-Making
Business Intelligence helps you make decisions on past results, and Data Analytics helps you make predictions that will help you in the future. In other words, Business Intelligence is needed to run a business while Data Analytics is needed to change a business. It’s the difference between knowing that you need to wear a bike helmet and understanding why wearing one is important. Innovative business leaders should take advantage of both in order to make informed and confident decisions.
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