Business Intelligence (BI)

Business Intelligence (BI)

What is Business Intelligence (BI)?

Business Intelligence (BI) refers to the procedural and technical infrastructure that collects, stores and analyzes data produced by the activities of a company. BI is a broad term that encompasses data mining, process analysis, benchmarking performance, and descriptive analysis. BI analyzes all the data generated by a business and presents easily digestible reports, performance measures and trends that inform management decisions.

Business Intelligence (BI) explained

The need for BI stems from the concept that managers with inaccurate or incomplete information will, on average, tend to make worse decisions than if they had better information. The creators of financial models recognize this as a “trash inside, a trash in the trash”. BI is trying to solve this problem by analyzing the current data which is ideally presented on a dashboard of rapid measurements designed to make better decisions.

Most businesses can benefit from the integration of BI solutions; managers who have inaccurate or incomplete information will, on average, tend to make worse decisions than if they had better information.

The growing field of Business Intelligence

To be useful, BI must seek to increase the accuracy, timeliness and amount of data. These requirements involve finding more ways to capture information that is not already recorded, checking the information for errors, and structuring the information to allow for broad analysis.

In practice, however, companies have data that is unstructured or in various formats that does not facilitate collection and analysis. Software publishers thus offer business intelligence solutions to optimize the information gleaned from the data. These are enterprise-level software applications designed to unify enterprise data and analytics.

Although software solutions continue to evolve and become more sophisticated, data scientists still need to manage the trade-offs between speed and depth of reporting. Some big data information drives companies to do whatever it takes to capture everything, but data analysts can usually filter sources to find a selection of data points that can represent the health of a process or business area in general. This can reduce the need to capture and reformat everything for analysis, which saves analysis time and increases the speed of reporting.

Key points to remember

  • BI represents the technical infrastructure that collects, stores and analyzes company data.
  • BI analyzes data and produces reports and information that help managers make better decisions.
  • Software publishers produce BI solutions for companies that want to use their data better.

Business Intelligence (BI) explained

The need for BI stems from the concept that managers with inaccurate or incomplete information will, on average, tend to make worse decisions than if they had better information. The creators of financial models recognize this as a “trash in, trash can”. BI is trying to solve this problem by analyzing the current data which is ideally presented on a dashboard of quick metrics designed to make better decisions.

Benefits of Business Intelligence

There are many reasons why companies adopt BI. Many use it to take on functions as diverse as hiring, compliance, production and marketing. BI is a basic business value; it is difficult to find an industry that does not have better information to work with.

Some of the many benefits that companies can experience after adopting BI in their business models include faster and more accurate reporting and analysis, better data quality, better employee satisfaction, reduced costs and revenue and the ability to make better business decisions.

Quick fact

BI was derived to help companies avoid the problem of “incoming and outgoing waste”, which is the result of inaccurate or insufficient data analysis.

If, for example, you are responsible for the production schedules of several beverage factories and sales are showing strong month-to-month growth in a particular region, you can approve additional shifts in near real time for you. ensure that your factories can meet demand.

Likewise, you can quickly slow down that same production if a cooler than normal summer starts to affect sales. This manipulation of production is a limited example of how BI can increase profits and reduce costs when used correctly.

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