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.

Unstructured

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

Semi-Structured

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

Structured

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
  • MSSQL

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.

FAQs

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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The best way to gain a competitive edge in any industry is by knowing more about your operations and the market dynamics affecting them than your competitors. Competing with greater intensity and the ability to get more done in less time is what differentiates market leaders from other companies. One of the best ways to make this goal a reality is to implement a business intelligence tool with predictive analytics. But what is it? How is it implemented? How is it different from other kinds of analytics? Read on to answer these questions and more.

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Does your business have a system in place for creating reports? If so, can the current system manage the size and complexity of data as your business grows? At the enterprise level, it is necessary to adopt a system specifically made for reporting in an enterprise environment. Enterprise reporting software serves this purpose, and specific reporting tools features and functionality cater to the needs of your organization.

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The internet of things, one of the buzziest buzzwords of our time, envisions a vast network of interconnected devices — from those in our homes to the ones in our pockets. But if we think about it, companies aren’t using the internet of things (IoT) just for fun gadgets. It’s actually serving many businesses and changing the way they work. IoT analytics have enabled a whole new world of business intelligence tools that speak to each other and to you in order to make your life smarter, faster and easier.

This article will explore the possibilities that can be pursued when business intelligence and the IoT collide. We’ll break down this buzzword, highlight a couple examples of businesses that have made the leap to combining advanced analytics and the IoT. We will also lay out the benefits and some highlights of the wide world of IoT analytics.

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As today’s modern businesses attempt to become more data-driven, they adopt business intelligence (BI) to make sense of all the data they collect. You’ll find businesses of all sizes in all industries using BI tools to optimize their processes and make better decisions, including those in the healthcare industry. Through BI, the massive amount of data that the healthcare industry generates can be analyzed and transformed into impactful actions that improve performance and quality of care. We’ll take a look at what healthcare BI is, what it does, what benefits it provides, as well as a list of the best healthcare BI software tools currently available on the market.

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Tableau is a cornerstone of the BI tools market with over 86,000 users as of 2019. A self-service analytics platform well-known for its accessible, interactive dashboards, Tableau’s reputation often precedes itself. That being said, it isn’t right for everyone, but luckily, there are plenty of options out there. Our analyst team scoped out the competition and identified the top five Tableau alternatives. Read on to see what the Tableau competition looks like, how Tableau competitors compare and how to choose the best one for you.

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Business intelligence makes sense of the modern data landscape, which grows increasingly more complex and digitized. It follows that picking the right BI tools for your company makes all the difference in deriving meaningful insights from your data and making better business decisions. So how do you choose? Comparing industry leaders can be a good place to start, so we compared three of the top BI tools on the market to help guide you in your software selection process. Without further ado, let’s look at a features-to-features comparison of Power BI vs Tableau vs QlikView and see which one has the advantage in each category.

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KPIs are one of the most powerful tools an organization can harness in their business intelligence efforts. As the name suggests, key performance indicators, or KPIs, are metrics that are used to monitor business activities that are critical to the success of the company. They help to quickly cut through the massive amount of information that constitutes day-to-day business operations to retrieve key insights. This last point is especially crucial, as it allows businesses to make adjustments in real-time. For this reason, in particular, many companies are looking into KPI software tools as a means of maintaining a consistent pulse on their business performance.

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Nowadays, companies have many options at their disposal to turn raw data into actionable next steps with business intelligence software. Some data mining tools can speed up this process through machine learning algorithms. Data mining in the modern age goes above and beyond simple data analysis to extract useful information from huge data sets in smarter and more effective ways than ever.

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Business intelligence (BI) is the practice of blending and visualizing proprietary enterprise data to discover trends and patterns that can help businesses make better, data-driven decisions. In today’s digital age where data rules supreme, picking the business intelligence software that will turn your data into actionable insights can be a critical choice that impacts your company for years to come. Since BI solutions span across the whole spectrum in terms of cost and features, it can be difficult to evaluate all your options and find the right one, but taking the time to do so properly can be one of the best investments of time you can make for your business. The evaluation process starts by gathering a template of business intelligence requirements; these requirements determine what you need to look for in a vendor.

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Data, data, data: In today’s business world, we create and transfer massive amounts of data constantly. From a business standpoint, having access to this much data presents a multitude of opportunities, but how can we turn data into action? The answer: using business intelligence. Business intelligence refers to a type of solution that collects and merges data, creates visualizations of datasets, discovers trends and insights hidden within data and helps users make data-informed decisions.  There are many subcategories of BI tools that target more specific needs; one of these kinds of tools is statistical software.

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A picture is worth a thousand words — or so the saying goes, right?

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In today’s hyper-competitive business world, only decisions that are backed by data can be trusted to bring the desired results. But in order to gain valuable insights from their data, companies must first understand it, and that’s very difficult if you aren’t able to visualize the data in a way that makes it easy to understand. That’s where business intelligence software and data visualization tools come in.

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The Business Intelligence (BI) software industry is quickly emerging as one of the top software categories in terms of market size. Gartner expects global revenue of BI to rise to $22.8 billion by 2020, and Reuters foresees additional growth to $29.48 billion by 2022. The business intelligence market is booming and will continue to do so as the market for BI solutions grows.

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While the average person might balk at the phrase “embedded business intelligence (BI) and analytics,” you’re not the average person. You’re looking for embedded analytics software or looking to learn more about it, and you’ve come to the right place! We’ve compiled an embedded analytics requirements checklist to help guide you in your search for embedded BI software.

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You’ve probably heard the saying, “work smarter, not harder.” That turn of phrase might as well have been invented for BI tools. Business intelligence software (BI) is comprised of a range of data analytics tools designed to analyze and manage data related to your business operations. So what are the benefits of business intelligence software? Some business intelligence benefits include rich visualization capabilities that allow businesses to monitor sales, logistics and even productivity. It also provides extensive data analysis using richly visualized, intuitive reports.

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Have you ever wished you could get a glimpse into the inner workings of your organization to understand more about how and why things happen? Well, I’ve got great news for you — you can! Business intelligence tools give you just this opportunity, but they can do much more! For those who’ve wondered what BI is good for, this article highlights the four main business intelligence applications and what it can do for your business.

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“I love to read through thousands of rows of data tables to digest information,” said no one ever. Most of the data you collect through business analytics tools end up in some kind of standard table of rows and columns. Although you could leave it in this form, it’s not only boring to look at, but also incredibly difficult to actually understand the big picture. Sure, you may get a general sense of what the data holds — you may even be able to spot a pattern or two. But to get a true picture of the story your data tells, you need visual analytics tools.

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Businesses are trying to harness the right data sets and analyze them in the right ways to make good decisions about products, services, customers, suppliers and much more. But BI tools come in so many forms, and the choices can be overwhelming. One of those choices is whether to pursue this business intelligence in-house or utilize new cloud or SaaS BI tools.

This article will attempt to explain what SaaS (software-as-a-service) business intelligence entails, the difference between on-premise and SaaS, some of the pros and cons of choosing a SaaS solution, and how to select the right BI tool for your business.

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Companies of all sizes and industries are looking to innovative business intelligence and analytics platforms to help them utilize internal data and perform a modern approach to data analysis. Excel is a great starter took, but it has its limits. It’s not great for data visualization, and doesn’t provide customers with enough robust analytics. Self-serve BI tools, therefore, are key to how competitive companies do business successfully, enabling better visibility in terms of sales, revenue, human resources and more.

Among the many BI solutions out there, Tableau and Domo are two of the most popular choices – one a mainstay and the other a newer entrant into the BI market. Here are some key features to understand when comparing these solutions:

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