Data has never been more critical to companies. Storing, analyzing, and putting them to good use are tasks that technology helps us do, and you have probably heard both terms: Business Intelligence and Business Analytics. But what is the difference, and how do you know if your company should choose BI or BA?
Follow the reading by the data scientist course in Bangalore and also know what to expect from each technology and what they have in common.
What Is Business Intelligence?
A research institute of the North American market defines BI as methodologies, processes, architectures, and technologies that help companies handle data. By inserting information in these tools, we can manage and visualize them better, create reports, check the performance of each area of the business, and organize the knowledge we have.
In general, BI software has tools that make querying (questions to validate what a data means) and generate reports, counting on a dashboard that translates this data into easy-to-understand graphs.
Although the term BI is quite broad, it is mainly used to generate insights based on historical data in business. Most software can be obtained in isolation and integrated with systems that a company already uses (CRM and ERP).
The main difference between how BI and Business Analytics handle data are interactive dashboards that, in Business Intelligence, help the user to understand the data he has.
We can simplify things by saying that BI systems work similarly to a FAQ for internal data. Users ask questions and get answers that are presented in such a simple way that even the person least used to dealing with them can understand them.
Therefore, BI shares access to information that previously would have been restricted to IT departments.
What Is Business Analytics?
Business Analytics is a way to take BI intelligence a step further. It approaches data science, applying the patterns identified in the information that a company uses to feed the software in predicting predictive models.
Applying Artificial Intelligence with Machine Learning or Cognitive Computing, Business Analytics can anticipate the future of the business in aspects as complex as customer retention.
It can also be applied to routine processes, such as fraud detection in financial institutions, much faster than any other technology.
By examining data with more sophisticated tools, BA creates what we call deep insights and can point, based on historical data, to a roadmap for the future.
Business Analytics algorithms do not have the sole task of analyzing data based on predetermined rules. They process raw data and apply it to understand correlations, relationships, patterns and thus generate predictions that lead to different and more accurate decisions.
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