Business intelligence - definition & overview

Business intelligence, sometimes abbreviated BI, is a broad term that describes the set of processes that business use to analyze the data that they generate through operations and turn it into actionable insights that can drive effective business decision-making.

The primary purpose of business intelligence is to report on the performance of internal and external systems in a timely way. Business intelligence software applications make use of dashboards, reporting and data visualization features that make it easier for decision-makers to quickly understand and interpret data.

On the surface, business intelligence and business analytics seem like nearly identical concepts. Both use technology-supported processes to extract value from organizational data and there can be significant overlap in the statistical techniques and methodologies used in each discipline. Still, there are a few key differences of which business owners and IT organizations should be aware.

Business analytics is often modeled as having four distinct stages: descriptive, diagnostic, predictive and prescriptive analytics - although, some sources include additional types, such as decision analytics or planning analytics. In the four-stage model, descriptive analytics is used to aggregate and summarize historical data that may yield useful insights and information. This is exactly the function of business intelligence, so it can be said that business intelligence and descriptive analytics are the same things. In that sense, business intelligence is a sub-part of business analytics.

Business intelligence does not include diagnostic functionality or predictive algorithms. It provides answers to concrete, fact-based questions such as:

1. What was the sequence of events that happened?
2. When did the events happen?
3. Who was involved in the event?
4. How many people were affected? How many times did the event occur?

Business intelligence includes a variety of applications, each of which can deliver specific benefits to the business organization. Regardless of the specific methodology, the over-arching goal of business intelligence is the same: to enable effective decision-making through the discovery of strategic, tactical and operational insights that are derived from data. Here are four simple ways that businesses can benefit from the effective implementation of BI:

Establish benchmarks and monitor performance

If a manager at a business wishes to measure the improvement over time of a given process, the first step is to establish a benchmark for the performance of the process. An organization might use competitive intelligence to benchmark its performance against that of a competitor, but it could also employ business intelligence to establish a benchmark based on its own performance of the chosen activity or process. Once the project has begun, business intelligence tools can be used to monitor the process and measure ongoing improvements.

Reduce wasted effort through knowledge management

IT organizations that have adopted the ITIL® framework of best practices for managing IT services will be familiar with the knowledge management process, whose goal is to reduce or eliminate the need for an organization to re-learn information it has already discovered. In the knowledge management process, organizations collect data, contextualize it into pieces of information, analyze it to discover knowledge and distill collected knowledge into wisdom. Business intelligence activities are a valuable input source for the knowledge management process.

Inform strategy with streamlined reporting

Business intelligence software tools offer streamlined reporting and dashboard features that condense the time between the generation of data and its presentation to executives or managers in a comprehensible and visually digestible format. A shortened delivery cycle for reporting on key performance indicators and other factors means that decision-makers can make better strategic decisions based on the most current information.

Leverage advanced analytical techniques

As we saw earlier, business intelligence is analogous to the descriptive analytics aspect of business analytics. Organizations that implement business intelligence software tools to increase the visibility of KPIs and performance metrics already have the systems in place to leverage their data using advanced analytical techniques, including predictive and prescriptive analytics and other analytical methods such as data mining, business process modeling and complex event processing.

Business intelligence software tools make it possible for organizations to extract value from their big data sets in the form of actionable insights. These tools incorporate features that enable alternative methodologies for extracting and delivering business intelligence. These features include things like:

Dashboards are a critical component of most business intelligence software tools, as they enable the user to reference data at-a-glance and quickly find important or relevant information.

Static reporting captures data at a specific point in time and consolidates the relevant parts into a static report that can have both textual and visual components. Static reports reflect the underlying data at the time of their creation, whereas dynamic reports check the database for new changes and update each time the report is created. Time-based reports, such as daily activity reports are usually presented in a static reporting format.

Ad Hoc analysis is essentially a customized reporting process used to generate novel reports that are not part of an IT organization's regularly scheduled reporting requirements.

Data visualization software enables the user to design graphs, charts or infographics that can present data in a unique, appealing and easily digestible way.

Sumo Logic's cloud analytics platform offers robust business intelligence functionality. Using machine learning and pattern recognition, organizations can aggregate huge volumes of data to analyze key performance metrics. Organizations also gain access to advanced analytical capabilities, including predictive and prescriptive analytics.