Business intelligence is a term that “includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information” (Gartner). It was born out of the 1960s decision support systems and then expanded upon and developed in the 1980s. Business intelligence emerged alongside computer models for decision making and planning as a way to turn data into conclusions. Although business intelligence has developed over time, it is still as important as ever.

This article should serve as an introduction to the topic, if you'd like to learn more, there are tons of books about business intelligence. We also have a list of real-world examples of business intelligence in action.

What is business intelligence?

Business intelligence is a technological term that overlooks data, computing, and analytics within business operations. Much more than a specific “thing,” business intelligence is rather an umbrella term that covers the processes and methods of collecting, storing, and analyzing data from business operations or activities to optimize performance. All of these things come together to create a comprehensive view of a business to help people make better, actionable decisions.

Examples of business intelligence:

  • Data mining
  • Reporting
  • Performance metrics and benchmarking
  • Descriptive analytics
  • Querying
  • Statistical analysis
  • Data visualization
  • Data preparation

Why is business intelligence important?

Simply put, business intelligence helps people make better business decisions by showing present and historical data within its business context. It offers performance benchmarks to make the business run smoother and more efficiently. It helps people spot market trends to increase sales or revenue. Used effectively, it can even help with compliance and hiring efforts. Just about any aspect of business can be improved through business intelligence.

Digital transformation has created a massive influx of information and it’s not slowing down. Data is everywhere, all the time—and it is now deeply entrenched into business processes for organizations of all sizes. Now everybody expects to be able to access and use new information to inform day-to-day decisions and quench their business curiosity about new avenues to pursue.

How business intelligence can help businesses:

  • Identify areas or ways to increase profit
  • Analyze customer behavior
  • Compare data with competing businesses
  • Track company performance
  • Optimize company operations
  • Predict success of new ventures
  • Identify market trends
  • Identify any business issues or problems

Example of an economic indicators dashboard, showing the long-term drivers of the U.S. economy
Example of an economic indicators dashboard, showing the long-term drivers of the U.S. economy.

How business intelligence works

Businesses have questions and goals. To answer these questions and track how they’re performing against these goals, they gather the necessary data, analyze it, and determine the actions they need to take to move the business forward.

For a practical example, financial services firm, Charles Schwab used business intelligence to see a comprehensive view of all of their branches across the United States to understand performance metrics and identify areas of opportunity. Access to a central business intelligence platform allowed Schwab to bring all of their branch data into one view. Now branch managers can identify clients that may have a change in investment needs. And leadership can track if a region's performance is above or below average and click in to see the branches that are driving that region's performance. This leads to more opportunities for optimization along with better customer service for clients.

On the technical side, raw data is collected from the business’ activity. Data is processed and then stored in data warehouses. Once it’s stored, users can then access the data, starting the analysis process to answer business questions.

The difference between business intelligence and business analytics

Business analytics is a subset of business intelligence. According to Gartner's IT glossary, “business analytics includes data mining, predictive analytics, applied analytics, and statistics.” In short, organizations conduct business analytics as part of their larger business intelligence strategy.

Business analytics shouldn’t be a linear process because answering one question will likely lead to follow-up questions and iteration. Rather, think of the process as a cycle of data access, discovery, exploration, and information sharing. This is called the cycle of analytics, a modern term explaining how businesses use analytics to react to changing questions and expectations.

Read more in our whitepaper about the cycle of analytics and other business intelligence terms.

Business intelligence tools

Many self-service business intelligence tools streamline the analysis process, making it easier for people to understand their data without the technical know-how to rummage through the data themselves.

One of the more common ways to present business intelligence is through data visualization. Humans are visual creatures and very in tune with patterns or differences in colors. Data visualizations present data in a way that is more accessible and understandable. Visualizations compiled into dashboards can easily tell a story and highlight trends or patterns that may not necessarily be easily discovered when manually analyzing the raw data. This accessibility also enables more conversations around the data, leading to broader business impact.

Read the report about evolving business intelligence trends.

The difference between traditional and modern business intelligence

In the past, business intelligence tools were based on a traditional business intelligence model. This was a top-down approach where business intelligence was driven by the IT organization and most, if not all analytics questions were answered through static reports. This meant that if someone had a follow-up question about the report they received, their request would go to the bottom of the reporting queue and they would have to start the process over again. This led to slow, frustrating reporting cycles and people weren’t able to leverage current data to make decisions.

The analytics workflow in the modern business intelligence model
The analytics workflow in the modern business intelligence model.

Today, more organizations are moving to a modern business intelligence model, characterized by a self-service approach to data. IT manages the data (security, accuracy, and access), allowing users to interact with their data directly through business intelligence platforms. Modern analytics platforms like Tableau help organizations address every step in the cycle of analytics—data preparation in Tableau Prep, analysis and discovery in Tableau Desktop, and sharing and governance in Tableau Server or Online. This means that IT can govern data access, while empowering more people to visually explore their data and share their insights.

Read this whitepaper about the modern approach to business intelligence.

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