An explanation of business intelligence

Long gone are the days of acting on gut feeling -- in the enterprise, at least.

Business intelligence, or BI, describes a technology-driven process that helps executives, managers and workers make informed, data-driven business decisions. It relies on advanced analytics, like data mining and predictive analytics, enabling businesses to monitor performance, detect trends and patterns in data, evaluate business decisions, and more.

Here, we'll discuss business intelligence use cases and benefits. For a detailed overview of business intelligence architecture, click the link above or in the description below. And remember to subscribe to Eye on Tech for more videos on all things business tech.

BI software emerged in the 1990s and, historically, required dedicated BI professionals to operate. But the development of AI and machine learning tools has made it easier for analysts and managers to use it themselves.

With the addition of self-service features and lower software costs, BI use has accelerated massively in the past few years, and for good reason. Modern BI tools and platforms can serve a variety of users, from C-suite executives to middle managers to operational workers.

Common functions include [the following]:

• Business monitoring, like tracking performance of the organization or a specific business unit to proactively identify and address problems.
• Data analysis, which might reveal business trends that opens new revenue opportunities.
• Reporting and information delivery, like interactive dashboards that give users control over which data to dig deeper into.
• Predictive analysis, which forecasts future events, like how customers might react to a marketing campaign.

Adopting a BI program optimizes business processes, helps find business problems that need to be addressed, identifies emerging market trends, provides companies with a competitive advantage, and drives higher sales and new revenues.

For example, it's used by [the following]:

• Banks to analyze financial risk during loan approval processes.
• Airlines to track flight capacity.
• Streaming services to understand customer preferences.
• Transportation companies to plan delivery routes and schedules.

But organizations must be prepared for challenges when applying BI, including [the following]:

• Fast but poor decision-making, if it was based on faulty or inaccurate data.
• BI project management, like training users, meeting data requirements, and managing self-service BI deployments.
• Getting user buy-in, especially if users are accustomed to other tools like Excel or aren't used to a data-driven culture.

BI is often used interchangeably with business analytics, or BA, but there are differences. While BI uses both past and current data to inform current decisions, BA uses past data to explain current data and predict what will happen in the future.

Overall, BI is an asset that bolsters business decision-making and mitigates risk. How do you use BI? Let us know in the comments, and remember to like and subscribe too.