What is business intelligence (BI)?
Business intelligence (BI) allows organizations to analyze and visualize all their data to spot trends and make smarter, more informed decisions.
It’s all about data. Business leaders hear that every day – but just collecting and storing data isn’t enough. Business intelligence actually puts your data to work, transforming it from zeroes and ones into meaningful insights. With BI, users can ask questions and get answers, clearly and instantly, to inform smart decision-making across your organization.
What is BI? Business intelligence definition
BI, or business intelligence, is a set of technologies and practices used to collect, analyze, and present business data to support decision-making. BI systems use data visualization tools to present findings in reports, interactive dashboards, and other formats that make the information easy to understand and share – no technical skills required.
Business intelligence and analytics
Together, business intelligence and analytics provide insightful information that can improve decision-making. And while they are closely related, they are not the same.
Business intelligence is descriptive and diagnostic in nature; it’s all about figuring out what happened, when, and why to help inform decisions. Business analytics is more concerned with what will happen, uncovering patterns to predict future trends – making it prescriptive and predictive. It can recommend actions to make desired outcomes happen, such as for forecasting demand for seasonal retail products or modeling different types of financial risk.
The tools they use also differ. In addition to data visualization tools, BI uses technology like OLAP processing, SQL, and ETL to dive into the data. In contrast, data analytics uses more advanced technologies like predictive modeling, machine learning, and data mining to spot patterns and make forward-looking predictions. These tools typically require people with technical skillset. Think data scientists, analysts, or IT teams.
BI and data analytics are both essential technologies for painting a full picture of all your data. That’s why many organizations turn to business intelligence platforms that support both types of analysis.
Benefits of business intelligence
Business intelligence gives organizations quick access to key metrics and reliable information, leading to a number of other advantages.
More informed decisions
Based on timely intelligence, metrics, and other information about business processes and operations, teams can make more confident decisions.
Faster reporting and analysis
With BI tools, interactive dashboards, and visual reports, teams can quickly explore and understand their data without having to wait for it to compile.
Improved operations
BI lets you check in on everything from inventory to supplier performance. It helps you identify areas for improvement and understand the reasons behind issues so you can address them.
Democratized data
Business intelligence systems bring data to everyone’s fingertips, not just to your data analysts or technical people.
Fewer data silos
By connecting BI-ready data across departments and systems, all teams can work from one reliable source of information.
Lowered costs
Because BI can help you quickly identify areas with excess waste, inventory, and other cost-drivers, you can take steps to reduce them.
More satisfied customers
With insights into factors like customer response times, resolution rates, and satisfaction scores, you can make positive process changes to engage customers.
The BI process: 5 steps to greater intelligence
Before business intelligence can deliver actionable information into graphs, charts, and other clear visualizations, it first has to transform raw data into meaningful insights. This is accomplished with multiple tools for integrating and storing data, modeling, querying, and visual analysis – all working together in a structured process.
STEP 1: Collect data
Data is gathered from a variety of sources – databases, applications, enterprise systems, and more. Depending on the BI solution used, this involves using connectors for ERP, CRM, MySQL, and other platforms or APIs.
STEP 2: Integrate and store data
Using extract, transform, load (ETL) or other processes, the relevant data is then cleansed, checked for quality issues, and put into a standardized format that can be read by BI and analytics systems. Finally, it is stored in a data warehouse, data mart, or data lake for fast analysis.
STEP 3: Analyze data
BI systems analyze data using techniques such as querying, OLAP processing, and data mining. Data modeling organizes information so it’s easier to work with and explore, while querying tools let you ask questions and get answers, sometimes in natural language. As a result of these analysis tools, you can group and filter data, compare statistics, and more.
STEP 4: Visualize and report data findings
Final insights are visualized into interactive dashboards, charts, graphs, and reports that distill complex information into easy-to-digest bites. Self-service BI tools allow business users to dig into their data without involving IT or having to wait for new fields to be updated.
STEP 5: Make confident decisions
Finally, organizations can explore all their data and act on valuable insights in real time to reap all the rewards that business intelligence has to offer.
BI reporting tools and dashboards
Business intelligence insights can be delivered through reports, visualizations, and dashboards. These methods can work separately or together and each is designed to support decisions in different ways. BI makes it easier to understand and act on your data whether you need high-level metrics or a deep dive into details.
BI reports
BI reports organize data into clear, shareable formats and support ad hoc reporting as well as scheduled reports. This lets users create one-off reports to answer questions or compare results across teams, products, or time.
Data visualizations
Charts, graphs, and visuals help you spot trends and patterns. They make sense of complex data and highlight what matters. The best BI platforms support user-friendly, drag-and-drop tools to create and update visuals quickly.
Dashboards
Dashboards combine reports and visuals into one interactive view. They can track KPIs, spot trends, and monitor performance. Dashboards customized by role or department ensure that the right teams always have the right insights.
Business intelligence examples in different industries
BI has broad applications across all sectors, offering targeted insights alongside cross-industry information. Here are just a few industry-specific examples:
Healthcare
Integrated insights from operational, financial, and clinical systems help nurses, doctors, and administrators build a complete picture of patient care. This holistic view supports improvements in everything from patient flow and resource allocation to staffing strategies and treatment patterns.
Manufacturing
Manufacturers can uncover valuable insights hidden within their production processes, machine performance, and operational data – such as equipment health and downtime. Monitoring KPIs for overall equipment effectiveness (OEE), defect rates, product-line financials, and other key metrics helps reduce waste, optimize maintenance schedules, and enhance product quality.
Automotive
Automotive companies gain critical visibility into production efficiency, supply chain health, and quality control. By tracking metrics such as defect rates, production cycle times, and supplier reliability, companies can identify bottlenecks early, streamline production schedules, and enhance vehicle quality.
Food and beverage
Producers and distributors can tap into data-driven insights about customer preferences, inventory turnover, and supply chain performance. Monitoring factors like seasonal demand fluctuations, ingredient costs, and spoilage rates helps optimize inventory management, reduce waste, and deliver consistent product quality.
The future of business intelligence
Business intelligence has evolved beyond simple reporting. It can increasingly be found embedded directly into workflows, apps, and devices to put relevant insights alongside day-to-day decisions. With voice-enabled queries and natural language search, business users will be able to interact with data as easily as asking a question out loud.
We’ll also see BI systems take on more active roles. When paired with technologies like machine learning and robotic process automation (RPA), they will not only surface insights but actually help you to act on them. For example, if the system detects a low inventory, it can automatically trigger a workflow for restocking and set it in motion.
Analytics tools are also growing smarter as predictive analytics continues to evolve. This means that beyond simply providing historical context, systems can offer real-time guidance. But as with any powerful technology, care is needed. As data pipelines grow more complex, you must also strengthen data governance to ensure transparency, build earned trust in AI-generated insights, and stay compliant with evolving regulations.
What to look for in business intelligence platforms
BI platforms offer capabilities across three categories: analysis, information delivery, and platform integration. Modern platforms combine all of these and more.
On the analysis front, look for OLAP or OLAP-like functionality that allows you to explore data across multiple dimensions, such as by region or time. You should also be able to drill down, roll up, pivot, and filter data with ease. Contemporary platforms achieve this using a virtual, in-memory analytical engine that doesn’t require having to manually build and maintain physical OLAP cubes – allowing for greater flexibility and less time and effort by IT departments. This type of platform also lets business users to generate ad hoc reports and build custom queries and dashboards on the fly. A shared semantic layer allows for consistent and accurate data analysis by standardizing business terms across departments.
And of course, no platform today would be complete without advanced analytical capabilities and augmented analytics for analyzing trends, forecasting, running “what-if” scenarios – and making AI-driven predictions.
To get the most impact out of BI, look for a variety of outputs. Interactive dashboards, charts, KPIs, and enterprise reports are pretty standard, but you can find platforms that support other types of visual data discovery, geo maps, tables, and embedded analytics.
Platform integration is also critical. A cloud-based data architecture should be able to connect live data from any source, unify big data, integrate data lakes and APIs, and centralize data governance. Look for built-in AI technologies to give your business intelligence systems a sharper edge.
Discover how Infor Birst – our cloud analytics platform with BI capabilities – can help everyone in your organization make smart data-driven decisions in the moment.
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