The Starter Guide to Business Intelligence

Emily Hayward

This article is a part of our Starter Guide series. Check out the Starter Guide to Dashboards and The Starter Guide to Dashboard Design.

So you’ve got data, but what do you do with it? How do you distill the data into something tangible? We’ve all asked this question at one point or another.

The influx in available data has piqued data-curiosity. How can you use the wealth of data that is available to you to influence decisions?

You’ve likely heard the term Business Intelligence, more commonly referred to as BI. Literally, business intelligence means being more intelligent about your business. And your approach to BI is defined by the tools you use. Examples of BI tools include data warehouses, dashboards, reports, data discovery tools, and cloud data services. These tools make it possible to extract the insights from your data.

And then there’s the engine that fuels BI tools: the data itself.

There’s no doubt that the Internet of Things (IoT) has changed the way that the general population can access data, too. Data is available at the click of a button. Whether it’s fitness stats from your smartwatch or monthly recurring revenue for a large enterprise business, there is data everywhere.

Do you or someone you know have a smartwatch or fitness tracker? These devices track simple performance metrics like daily steps, standing hours, and exercise minutes. And consider the insights available in that data: Maybe you need to increase your step count to meet a goal? This data can help you make decisions as to how you approach fitness.

When it comes to data, it’s up to you to decide how you want to use and interpret it (consumer or business), analyze it, and make data-driven decisions. That’s BI in action.

The business intelligence industry

Business intelligence software are the tools that make it possible to create value from your data, like dashboards or reports. BI tools typically provide historical and current data in context to enable informed decision-making and prediction development.

The business intelligence industry moves quickly to keep up with the pace of change and demand from its users. In fact, 54% of enterprises cite that cloud business intelligence (cloud BI) is critical or very important to current and future strategies.

Business intelligence creates order in a chaotic data universe. Whether it’s data visualization or data warehousing tools, BI is about implementing a strategy to get more value from your data. And while that might sound scary, BI isn’t reserved for enterprise shops with hefty IT budgets—BI is used to democratize data and provide you with the most value from it, regardless of size or scope.

Throughout this guide, we’re going to unpack the facets of business intelligence. My goal is to make it simple—no fear of BI here. We’ll look at:

• Definition of BI
• History of BI
• Traditional versus modern BI
• Frequently used BI terms
• BI trends
• BI tools and how to pick the right one for you

Ready to jump in?

Definition of business intelligence

Wikipedia states that “Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis of business information. BI technologies provide historical, current, and predictive views of business operations.”

BI tools may have one or more of these functionalities:

• Reporting
• Analytics and dashboard development
• Online analytical processing
• Data mining and process mining
• Complex event processing
• Business performance management
• Benchmarking
• Predictive and perspective analytics

Now let’s look at business intelligence from the perspective of industry thought leaders and subject matter experts.

Hans Peter Luhn

IBM researcher Hans Peter Luhn is credited with coining the term Business Intelligence in 1958. Luhn defines BI as “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”

Howard Dresner

In 1989, Howard Dresner (later a Gartner Group analyst) proposed ‘Business Intelligence’ as an umbrella term to describe “concepts and methods to improve business decision-making by using fact-based support systems.”

Forrester

Forrester further builds off this idea with a broad definition of BI: “Business intelligence is a set of methodologies, processes, platforms, applications, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making.”

Wayne Eckerson

Wayne Eckerson’s concept is simple: “BI consists of two diametrically opposed activities: top-down, metrics-driven reporting, and dashboarding where you know in advance what things you want to monitor, and bottom-up, ad-hoc analysis to answer unanticipated questions.”

BeyeNetwork

The BeyeNetwork published an article by Larry English where he emphasizes that “Business Intelligence requires information quality.” He then goes on to propose this definition of BI: “The ability of an enterprise to act effectively through the exploitation of its human and information resources.”

Now that we’ve defined BI and heard from the thought leaders, let’s look at a brief history of business intelligence and how far it's come.

The history of business intelligence

1958: IBM researcher Hans Peter Luhn publishes “A Business Intelligence System.” Hans is later named the father of business intelligence.

1970s: The emergence of BI vendors with tools that are meant to help access and organize data.

The 1980-90s: First-generation BI

1988: The Multiway Data Analysis consortium, an international conference to streamline data processes, is held in Rome.

1989: Howard Dresner defines BI as we know it today: “Concepts and methods to improve business decision-making by using fact-based support systems."

1989: The term “business intelligence” gains traction and becomes widespread.

Early 2000s: Second-generation BI

2005: With social media platforms like Facebook and Twitter on the rise, the amount of data created and made available skyrockets.

2008: Business intelligence, analytics, and performance management revenue reached $8.8B.

2010: 35% of organizations employ pervasive BI. 67% of “best in class” companies have some self-service BI.

Today, the next-generation of BI

2017: Augmented analytics—the ability to automate insights using machine learning and natural language generation—is predicted as the future of data and analytics by Gartner.

2018: Cloud BI adoption skyrockets to 49%, nearly doubling adoption levels of 2016 (25% of enterprise users).

2021: The global BI market size is projected to reach 27870M USD by 2026 (from 18720M USD in 2019).

Traditional BI versus modern BI

Historically, business intelligence was a function owned by IT. This led to a top-down approach for reporting and analysis. Decision makers would have to ask gatekeepers for an analysis or report, creating a barrier to access real-time reporting and insights.

As the functionality and software has transformed, so has the ownership. Modern BI is a core business function that is accessed and owned across the organization. One of the core benefits of modern BI is accessibility. Users can access and interact with the data in real-time and create reports and dashboards almost instantly, removing barriers to entry.

Now, business intelligence encompasses the tools, methodologies, and technologies that enable self-serve analysis. It can be as simple as logging in and accessing dashboards, reports, and analytics that transform data points into digestible insights.

Modern business intelligence will help you and your team:

• Access answers to critical business questions
• Align activities with strategy
• Reduce time spent on data entry and manipulation
• Gain in-depth, real-time insights into customers
• Benchmark your data against competitior and historical data for continuous improvements
• Identify and analyze areas to cut costs and to allocate budget
• Boost internal productivity by spending time on what’s important

Frequently asked BI questions

Let’s take a look at some of the terms you may hear associated with business intelligence and what they mean for you.

What is a dashboard?

A dashboard is a visual information management tool that tracks, analyzes, and displays key performance indicators, metrics, and data points to monitor the health of a business, department, or specific process. Dashboards are customizable so you can design them to meet the specific needs of your department or company.

Behind the scenes, a dashboard connects to your files, services, APIs or attachments, and displays this data as tables, charts, or other data visualizations to the viewer and reduces manual effort.

What is a KPI?

A Key Performance Indicator, or a KPI, is a measurable value that demonstrates how effectively a company is achieving a key business objective. KPIs can be used at any level, from individual contributors to executives, to evaluate the success of reaching targets. KPIs are evaluated over a defined period of time and compared against past performance metrics or acceptable norms.

KPIs can focus on high-level business performance or look at the processes in individual departments, like marketing, sales, HR, or development. You can check out our full guide to KPIs here.

What is a metric?

A metric is a quantifiable measure that is used to track and assess the status of a specific process. It’s worth noting that you may see metric and measure used interchangeably, but there is a difference: a measure is a fundamental or unit-specific term, whereas a metric can be derived from one or more measures. Therefore, metric has a goal or performance nuance associated with it.

What is a report?

In its simplest form, a report is a static document that presents information in an organized format for an intended audience or purpose. Reports provide information or communicate context, support problem-solving and decision-making, and outline planning and policies. Reports can be exported from business intelligence tools for easy distribution and information sharing.

Are you currently building your reports across numerous spreadsheets? BI tools allow you to automate your reporting, too, so you can shift your focus to other tasks or responsibilities while still sharing key business information.

What is data visualization?

Data visualization is the process of displaying raw data in a visual manner that can be understood by viewers. If your readers are asking questions about the data (rather than how or what is displayed), that’s a good indicator that your visualization is on-point!

There are 5 types of data visualization categories:

1. Temporal: This type of visualization is linear and one-dimensional. Examples include scatter plots or line graphs.
2. Hierarchical: This type of visualization orders groups within larger groups and are best suited for clusters of information like tree diagrams, ring charts, or sunburst diagrams.
3. Network: This type of visualization shows the relationship between datasets without wordy explanations. Examples include matrix charts, node-link diagrams, and word clouds.
4. Multidimensional: This type of visualization has 2 or more variables to create a 3D visualization. Examples include pie charts, Venn diagrams, and stacked bar graphs.
5. Geospatial: This type of visualization relates to physical locations and overlays familiar maps with data points. Examples include flow map, cartogram, and heat map.

No matter what type of data visualization you choose, it will tell an insightful data story. When you put a data visualization on a dashboard, you create an easy avenue for people across your organization to access and understand your business data. And remember: you’re the artist when it comes to creating visualizations. Consider colours, icons, and overall design for easy reading. Get a full breakdown of data visualization types in our expansive data visualization guide.

What is data analytics?

Analytics is the systematic computational analysis of data or statistics for the discovery, interpretation, and communication of meaningful patterns in data.

According to Investopedia, data analytics “is the science of analyzing raw data in order to make conclusions about that information.” Analytics is highly interactive and provides an opportunity to explore live and historical data. Typically, analytics focuses on one metric with as much depth and richness as possible. Analytics is rooted in exploration to understand your data, identify patterns and learn.

What's the difference between reporting, dashboards, and analytics?

Now that we’ve defined the terms above, you may be noticing similarities. So let’s take it one step further. What’s the difference between a report, a dashboard, and analytics?

ReportsDashboardsAnalyticsStatic

Interactive
Historical dataLive data (sometimes predictive)
Brings multiple metrics together
Focused on one metric (with depth and richness)

Sharing information on known areas of interest and goals

Monitoring known areas of interest and goals

Exploring unknowns to understand, find patterns, and learn

Business intelligence trends in 2021

Let’s take a closer look at what trends are gaining traction in BI in 2021.

No-code

The no-code movement empowers people without technical or data analytics skills to succeed—no developer or data analyst required! Anyone can import and modify data and visualize, filter, or segment—all without writing a single line of code. No-code empowers everyone to be data-driven and we’re here for it. Examples of popular no-code tools include Airtable, Zapier, and Typeform.

Self-serve analytics

Reporting on business insights is no longer exclusively reserved for data analysts. Modern BI tools are flexible and enable self-serve analysis. Instead of creating reports from data that lives in spreadsheets and presentation decks, you can easily login to your BI software and gather the digestible and actionable data you need. You no longer need a data analyst or IT title to access and design reports.

Lightweight BI

Traditional BI solutions are often complex, inaccessible, and require technical expertise to access information. Lightweight BI bypasses that cost and complexity.

Lightweight BI is often low or no-code, which means you don’t have to have any technical chops. Lightweight BI is also quick and easy to set up. In a lightweight BI tool like PowerMetrics, you can choose from a library of curated Instant Metrics and build a dashboard in 10 minutes or less—all you need are your login credentials.

Lightweight BI also has the power to visualize data into charts, or filter and segment at the click of a button so you can explore the data to its fullest extent. The key to lightweight BI is that anyone can use it and be successful.

Data democracy

There’s no doubt that being able to glean insights from data means you can make smarter, informed business decisions. Data democracy removes barriers to access so that everyone can use data to drive strategic decision making.

According to Dataversity, data democracy is formed by these principles:

1. The average user can access information in any digital format
2. Non-specialists can gather and analyze data or self-serve without requiring specialized help
3. Individual private data needs to be protected (for example, GDPR and CASL)
4. Data quality is a must
5. Technologies like Augmented Analytics, NoSQL, dashboards and self-service tools (like Klipfolio!) are pillars in empowering non-technical people in data democracy
6. Data ethics need to guide data democracies

Ultimately, data democracy creates a space where employees from across the entire organization are aware of data, have access to data without gatekeepers or barriers, and can participate in using the data in their day-to-day work and decision-making.

How to pick the right BI tool

As mentioned at the beginning of this guide, BI is advancing rapidly to become more accessible and easier for all businesses. The businesses that leverage the power of BI undoubtedly have a competitive edge over those who don’t.

Business intelligence empowers your employees as much as it empowers your business. Companies have found that allowing employees to access and track analytical and operational data improves work efficiency and goals by monitoring real-time efforts alongside a business plan. The power of BI provides your teams with the opportunity to tell their data stories, work faster and smarter, and embrace an open and transparent workplace. It takes your organization to the next level.