Business Intelligence

What is BI?

What is Business Intelligence?

BI Helps You:

  • Collect proprietary business data
  • Blend data from a variety of sources
  • Create intuitive visualizations of datasets
  • Discover data trends and patterns
  • Glean insights from data
  • Make informed, data-driven business decisions

Collect proprietary business data

Whether you realize it or not, your organization is producing data almost constantly. In the past, all of this information would have simply vanished as wasted potential.

With the use of BI tools, that valuable raw data can be collected, stored, organized and structured into usable information.

This data can incorporate a range of information types. Some kinds of data users should consider collecting are:

  • Sales metrics
  • Customer demographics
  • Employee quotas
  • Social media followers
  • Social media engagement
  • Customer behavior data
  • Retention rates
  • Conversion rates

These are by no means the only kinds of data you can begin to utilize through business intelligence, but they are some of the most common.

Blend data from a variety of sources

Another key component of business intelligence is where it draws all that data from. BI draws data from a variety of sources and blends it into a cohesive pool in the user’s data warehouse. These sources come in three formats: unstructured, semi-structured and structured.


This kind of data is any kind of data that is not organized into a relational database. It can be difficult to transfer directly into information users can interpret, but it doesn’t have to be. About 90% of data is unstructured and needs to be put through some kind of organizational process to be usable. Some examples of this type of data are:

  • PDFs
  • Images
  • Videos
  • MP3s
  • Movies
  • Emails
  • Websites


This is an in-between category. If a dataset isn’t necessarily organized into a relational database but also isn’t completely unorganized. It typically has some sort of regulation system that makes it easier to analyze without putting it into rows and columns. Some examples of semi-structured data sources include:

  • XML documents
  • NoSQL databases
  • JSON
  • MongoDB
  • CSV


Also sometimes referred to as relational data, structured data is comprised of easily-classifiable information stored in a relational database like phone numbers, zip codes, credit cards, birthdates, and other information that fits into easily pre-defined fields. Only about 5–10% of all data is structured before being put through an algorithm or software system.

Some examples of structured data sources are:

  • CRMs
  • ERPs
  • MySQL
  • DB2

Business intelligence can draw unstructured, semi-structured and structured data from these different sources and blend them into usable data in an organization’s data warehouse.

Create intuitive visualizations of datasets

Once the data is cleaned up and structured, BI software can generate graphical depictions of the data. It does this by creating a visualization of the data in the form of a scattergram, bar graph, pie chart, etc.

Many BI solutions offer a best-match suggestion to help users select the visualization type that will best depict the type of data. For example, a pie chart works best if the data is representing portions of a whole, bar graphs excel at comparing one variable against one or two others, etc.

Discover data trends and patterns

These visualizations help users uncover patterns and trends in the data. As a basic example, imagine a scattergram of your organization’s sales numbers charted against the 50 U.S. states. While you might be able to identify patterns in the report that only gives you sales per state, that information depicted graphically makes contextualizing those numbers much more intuitive.

The human brain interprets visual data much more quickly than abstract numerical data, so this process speeds up the time to insight and makes data analysis accessible for users from a range of technical skills and backgrounds.

Glean insights from data

Now that you have this hypothetical graph of your business’ sales in each U.S. state, you can use the patterns depicted in the visualization to glean insights. Let’s say your sales are generally good in the West, but poor in Washington and Oregon.

What could account for this discrepancy? Is there a market for your product or service that you aren’t fully taking advantage of? Are you wasting resources on a region that doesn’t have a need for your product or service? You can ask these kinds of guided questions to uncover new information and insights into your business that wouldn’t have been as apparent without BI applications.

Make informed, data-driven business decisions

Continuing our example, you have insight that sales are poor in the Pacific Northwest region of the U.S. You can use this information to shape your business strategy as you proceed. Do you need to target a new market? Do you need to invest more in advertising?

Many BI tools offer forecasting features that let users run scenarios based on different strategies. These use historical data to predict future results, allowing you to test hypothetical strategies before fully implementing them. Businesses that make data-driven decisions tend to be more confident, more successful and more in control of their path.


What Is the Purpose of Business Intelligence?

Business intelligence aims to improve users’ access to and control over their proprietary business data. Its goals are to deliver actionable insights, improve data literacy and facilitate data-driven decisions based on information unique to the company making them.

What Are the Benefits of Using BI Tools?

There are many benefits of business intelligence. Here are just a few:

  • Improve data literacy
  • Optimize internal business processes
  • Boost revenue
  • Gain a competitive edge
  • Identify problems within a business
  • Predict trends in the relevant markets
  • Encourage confidence in decision-making

For more information, see this article about the benefits of using a BI system.

How Do I Implement a BI System?

Implementing a BI tool is an intensive process, but taking special care to ensure it goes smoothly can pay off in the long term with significant ROI profitability. Some steps to ensure the implementation goes off without a hitch are:

  • Clean up your data
  • Give all users adequate training
  • Manage your expectations — it won’t be perfect right away
  • Check in with your ROI plan every few months to ensure you’re on track
  • Focus on your business objectives
  • Be patient with your employees

For an in-depth look at implementing a BI solution, see this article on how to build a BI strategy or this article about BI implementation strategies.

What Is the Difference Between Business Intelligence and Business Analytics?

While the two terms are occasionally used interchangeably, there are some basic differences between BI and BA. For example, BI performs:

  • Descriptive analytics
  • Diagnostic analytics

BA performs:

  • Predictive analytics
  • Prescriptive analytics

Basically, BI tends to focus on historical and present data, whereas BA specializes in extrapolating that data into forecasts and predictions. The two certainly overlap in many ways, but these semantic differences should help you keep them straight.

What’s the Difference Between BI, Big Data and Data Mining?

These terms are also often used interchangeably, but unlike BI and BA, there are many very distinct differences. BI is an umbrella term that includes business analytics, big data, data mining, embedded analytics and enterprise reporting under its expanse.

Big data is the term for huge sets of unstructured data — think the kind of browsing data Google collects from its users. BI processes big data and puts it through analytical processes to organize and understand it.

Data mining is a step BI uses to process data. It allows users to explore data and drill down into specific data points within larger sets. It lets them search specific queries within the system and draw out targeted results. For a more detailed comparison, see this article on BI vs. big data vs. data mining.

What Industries Use BI?

Almost every industry can benefit from analytics and reporting capabilities. Some of the most obvious are retail/wholesale, banking and advertising, but many others do as well. Healthcare, for example, is a quickly growing sector of the BI market as they use BI to identify trends and improve patient care. Check out this article for a deeper look into BI market insights.

How Do I Select a BI System?

The first step in implementing a BI tool is to analyze how you currently collect data (if at all) and how you make decisions. Consider what information would make those decisions easier and how much collaboration you’d like to have on that data. This should get you started, and this interactive business intelligence requirements checklist can familiarize you with the range of features available from BI tools.

Selecting which of these you will need to utilize most will help you narrow down a vendor based on how well they deliver those modules. This BI software comparison matrix can give you information on how the industry leaders compare in performance feature by feature.

Once you’ve used this tool to make a shortlist of viable vendors, you should submit a BI RFP to request pricing information, demos and specialized information on how a specific solution will meet your needs.

Want help figuring out which software vendor is right for you? We can help. Contact our support team for individualized recommendations at [email protected] or 877-692-2896.

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BI articles are written and edited by:

Hsing Tseng

Market Analyst

Hsing Tseng is a Market Analyst at SelectHub who writes content for Business Intelligence. She studied Journalism and Asian Studies at the University of Denver and has written for news organizations like FOX31 Denver and USA Today College.

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Mariah Hansen

Lead Editor

As the lead editor at SelectHub, Mariah edits and manages content for more than 40 different software categories, as well as writing for a couple of them herself.

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Thought Leaders

SelectHub has sought out and invited thought leaders to contribute to our BI industry articles and resources. These thought leaders ensure we deliver quality content with the most accurate information, focusing on what matters most. No thought leader is compensated for their contributions, but shares our belief that information should be democratized so everyone can make the best decision.

Shaku Atre

Shaku Atre

President, Atre Group, Inc.

“Shaku Atre has been a pioneer in computer science, as one of the first women practitioners of database design and related technologies to achieve prominence worldwide. Known for her practical expertise, she has been an entrepreneur, text book author
and trade press columnist. She has also been a key note speaker on a range of technology topics all over the world.”

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Ellis Booker

Ellis Booker

Co Founder, Finders Keepers

Ellis Booker is a familiar name in the computer trade press, where he held senior editorial posts at a number of A-list IT publications, including CMP’s [now UBM’s] InternetWeek, Mecklermedia’s Web Week and IDG’s Computerworld.

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Steve Hilton

Steve Hilton

Co-founder & President, MachNation

Steve Hilton is a co-founder and President at MachNation, the leading benchmarking and testing firm for Internet of Things (IoT) middleware and platforms. His primary areas of expertise include competitive positioning, marketing media development, cloud services, small and medium businesses, and sales channels.

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Greg Steffine

Greg Steffine

SVP and Director, Analytics Enablement, Key Bank

For more than 25 years now, Greg has worked as a business intelligence strategist and solution delivery leader to help business leaders use information to create and maximize value

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Mike Galbraith

Mike Galbraith

VP, Technology and Solutions, ThoughtFocus

Mike brings many years of experience as an IT executive and CIO, Digital Transformation Leader and Delivery leader for several Fortune 200 companies. His areas of expertise include global IT strategy, Enterprise Architecture, delivery and operations, Digital Transformation, ERP systems, IoT, Big Data and Analytics. At ThoughtFocus, Mike assists clients in developing capabilities to drive innovation and competitive differentiation.

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Matthew Pluster

Matthew Pluster

Director, Data Analytics, Skylinetechnologies

Matthew Pluster is the Director of Data Analytics and Data Platform Solutions at Skyline Technologies, an IT consulting firm that provides world-class solutions and services.

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Ryan Wilson

Ryan Wilson

CTO, Build Intelligence

Ryan Wilson is currently CTO of Build Intelligence, a Domo Consulting company specializing in the construction industry. Ryan has over 9 years of data analytics experience from a handful of positions in various industries ranging from biochemistry to early child care education to semi- conductors, etc.

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Mike Brody

Mike Brody

Serial Entrepreneur, Co-Founder and CEO of Exago Inc.

Mike Brody is a Serial Entrepreneur and Co-Founder and CEO of Exago Inc., makers of a web-based solution for software companies looking to provide ad hoc reporting, dashboards, and analytics to their internal and external customers.

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