What Are BI Tools? A Simple Definition + Examples
Sr. Content Marketing Manager, Sigma
Businesses that rely on data management tools to make decisions are 58% more likely to beat their revenue goals than non-data-driven companies. Today’s organizations generate a tremendous amount and variety of data via SaaS solutions, mobile devices, social networks, and more — and they’re eager to benefit from putting this data to use.
Business intelligence (BI) tools empower companies to understand data for smarter decisions that smooth the customer experience, inform product development, and improve operational processes. This post explores what BI tools are and offers examples of how companies use them to become more data-driven.
What Are BI Tools?
So what are BI tools, exactly? Using BI reporting tools, teams access, combine, and analyze data from across sources and then present insights in the form of summaries, reports, dashboards, and data visualizations. The goal is to provide decision-makers with actionable intelligence.
While reporting is a primary component of business intelligence and the dashboard is ubiquitous, BI is not merely report-generation. It’s important to go beyond the dashboard to gain an understanding of trends. Dashboards shouldn’t be stop signs for business users — decision-makers should be able to explore the underlying data for further insights.
Difference Between BI Reporting and Analytics Tools
The difference between business intelligence and data analytics is subtle, and these terms are often used interchangeably. But it’s worth noting the nuance since some business intelligence tools allow users to do both.
Business intelligence is primarily descriptive, showing events that happened in the past. In contrast, business analytics usually focuses on the diagnostic and prescriptive — why an event occurred and what’s likely to happen in the future based on different variables.
Some solutions like Sigma blur the lines between analytics and business intelligence tools since they empower non-technical users to do their own analysis. These tools are modern analytics solutions that are built for both technical and non-technical users alike. Business teams using Sigma, for example, are able to interact with a spreadsheet-like interface to dive deeper into the data and conduct what-if analyses — no code required.
How Businesses Use Business Intelligence Tools
While organizations use business intelligence tools in many different ways, here are two of the most common (and valuable).
Data analysis & exploration
With valuable data pouring in rapidly from so many different sources, today’s businesses need BI tools for real-time access on-demand. Daily micro-decisions add up to impact the company’s long-term success, so it’s important that these decisions be informed.
In order to be truly data-driven, today’s business teams must have the ability to dig directly into the data underlying reports to make decisions. With data analysis, users start with a business question they want to answer and then query and analyze relevant data to gain insights. They conduct what-if analyses to look at the impact of different variables and uncover novel insights that will drive the business forward.
Embedded analytics involves integrating reports, dashboards, and data visualizations into internal and external applications such as a CRM, ERP, or PMS. Embedded analytics allows you to authenticate users through those apps while maintaining data permissions from the BI tool. Users can access the insights they need when and where they need them without requesting a report from the data team. It also facilitates collaboration among different business teams and even outside partners.
Key Features of Business Intelligence Tools
For a company to benefit from a business intelligence tool, its people must be using it regularly. If a solution is difficult to deal with, it won’t get used. Here’s what to look for in a business intelligence tool.
First and foremost, you must be sure your tool facilitates compliance and ensures data quality with robust data governance and security features. Your business intelligence tool should sit atop your cloud data platform and use a secure connection to query your data warehouse directly, rather than extracting data. This ensures a single point of access for your data, which assists governance. Administrators should be able to set permissions by team and namespace, and restrict data access.
Your business insight software also needs to accommodate the volume and velocity of data coming in. Most businesses generate a lot of data from many different sources. They need a tool that’s built to seamlessly integrate with today’s cloud data platforms, which allow businesses to harness the scalability of the cloud, allowing analysis of data sets on the magnitude of hundreds of billions of rows.
It can’t be emphasized too thoroughly: non-technical users must have the ability to do their own analysis. If your business teams must be skilled in SQL or code to use your BI tool, they will have to go back to the BI team every time they have a question. The back-and-forth waiting game will hamper decision-making. With a tool like Sigma that allows users to work in a spreadsheet-based interface, ad-hoc reporting is simple and immediate.
Best BI Tools
Let’s take a look at a few BI tools and see how they aid business intelligence.
Cloud-native BI tools
Ideally, your BI tool will allow you to take advantage of the full capabilities of your cloud data platform, like Snowflake or Redshift. Improved speed and performance, more storage, and improved access will allow you to work with the massive amount of data you need to, at speed. Newer BI tools are cloud-native — they were built for the cloud, so they can seamlessly connect to cloud data platforms and make use of their capabilities.
Looker — Looker has its own proprietary modeling language called LookML, an alternate way to write SQL and define queries. For this reason, users need extended training. And even then, it’s not fully ad-hoc — questions asked outside of the data model must be programmed by the data team.
ThoughtSpot — ThoughtSpot is focused on AI analytics and robust embedding, but it’s not as good with prescriptive analytics.
Sigma — Sigma, of course, is a feature-rich yet simple-to-use cloud-native BI and data analytics platform that’s built for data specialists and business decision-makers alike.
Traditional BI reporting tools tools
Traditional tools have been around for a while, so they have name recognition, but they’re typically retrofitted for use with cloud data warehouses. This means that they have difficulty scaling, may choke on large datasets, and require extracts and summaries.
Tableau — Tableau is known for its data visualization features. But while it generates rich data visualizations and dashboards, users are restricted to pre-configured leaf levels that prevent true “What if?” follow-up analyses without the help of data and BI teams.
Microsoft Power BI — Microsoft Power BI is an established player with a robust community and an open-source repository of user-created visualizations. But the requirement to use DAX is limiting.
SAP Analytics Cloud — SAP Analytics Cloud was built for businesses that use the SAP database and data warehouse platforms. It’s popular with enterprise companies who prefer SAP.
A Strong BI Tool Is Your Ticket to Data-Driven Decisions
A BI tool that facilitates governance, is scalable, and makes it easy for non-technical users to conduct analysis will get your organization much closer to being truly data-driven. The right tool can inspire business users to get curious and dive into data for answers to everyday decision-making.
Explore Sigma’s business intelligence capabilities.