BUSINESS INTELLIGENCE AND ARTIFICIAL INTELLIGENCE - A COMPREHENSIVE ANALYSIS

Abstract

The procedural and technical infrastructure that collects saves, and analyses data generated by a company's activities is referred to as business intelligence (BI). Business intelligence encompasses data mining, process analysis, performance benchmarking, and descriptive analytics, among other things (BI). BI takes all of a company's data and organises it into easy-to-understand reports, metrics, and trends that help managers make better decisions. The technical architecture for collecting, storing, and analysing firm data is known as business intelligence (BI). BI parses data and generates reports and data that assist managers in making more informed decisions. Providers that want to make better use of their data turn to software companies for BI solutions. Spreadsheets, reporting/query software, data visualisation software, data mining tools, and online analytical processing are all examples of BI tools and software (OLAP). Self-service BI is a type of analytics that allows people with little technical knowledge to access and interpret data. The necessity for BI arose from the idea that managers who have erroneous or partial information make worse judgments on average than those who have superior information. Their powerful algorithms, sensors, and cameras are based on real-world experience, and they combine dashboards and visual displays to show information in real time so that human drivers can understand current traffic and vehicular situations. In the event of fully autonomous vehicles, advanced technologies are capable of fully controlling the vehicle and making all navigational decisions. AI isn't a far-fetched concept; it's already here, and it's being integrated and implemented across a wide range of industries.