5 Business Intelligence Tools You Need to Know

Written by Coursera • Updated on

These five essential BI tools can help you discover insights to make important business decisions.

[Featured Image] A man wearing a blue sweater, and glasses collecting and analyzing data sitting in front of his computer.

Just like a handyman needs a toolbox equipped with hammers, nails, and screwdrivers, individuals pursuing careers in business intelligence (BI) must be familiar with certain software tools. Business intelligence involves the functions, strategies, and tools companies use to collect, process, and analyze data.

Business intelligence tools can identify new opportunities for businesses to improve return on investment (ROI) and competitive advantage based on insights found. These tools are used across all departments and industries, so consider exploring one to accelerate your career.

Here’s a look at the benefits of BI tools and five of the most commonly used tools.

What is a business intelligence (BI) tool?

Business intelligence tools collect, process, and analyze large amounts of structured and unstructured data from both internal and external systems. Data sources might include documents, images, email, videos, journals, books, social media posts, files, and more. BI tools find this information through queries, which can present the data in user-friendly formats such as reports, dashboards, charts, and graphs.

The tools can perform functions such as data mining, data visualization, performance management, analytics, reporting, text mining, predictive analytics, and much more. As a result, employees can harness this information to make better decisions based on predictions, market trends, and key performance indicators (KPIs).

Benefits of BI tools

BI tools can help your business take smart, agile steps toward accomplishing bigger goals. 

Centralized data: All of your data, in one place. Companies collect data from numerous databases, portals, customer relationship management (CRM) systems, enterprise resource planning (ERP) systems, and more. To make sense of it all, you’ll need business intelligence tools to pool the data together and deliver certain types of views (issues, trends, analytics) based on your queries or what you want to know. 

Self-sufficiency: Data no longer just belongs to your company’s IT team. Now, any employee without technical expertise, even interns, can access and analyze data necessary for their respective teams. They can generate reports on all electronics sales in 2020 or visualize patient records to identify the number of COVID-19 cases in 2022.

Make predictions: With access to so much data from the past and present, employees can make evidence-based decisions. Predictive analytics and forecasting enable users to generate insights based on a product or service’s performance history. If a business condition changes, the intelligent tools can automatically figure out the anomalies and you’ll be able to react to disruptions as they arise. 

Automatic reports: Instead of inputting data manually into Excel spreadsheets or toggling between different tools, many BI tools are automated. If you need a report on a product over a specific period of time, the tool will generate that for you. If that information is significant and you want to add it to a presentation, you can create an interactive dashboard and download any charts or graphs you may need. 

Reduces business costs: BI tools can do so much, from analyzing consumer behavior and sales forecasting to real-time process monitoring, that analyzing, planning, and reporting processes are way more efficient and accurate than ever before. In fact, more than 50 percent of BI tools users reported that these benefits helped them reduce costs and increase revenue [1].

Top 5 business intelligence tools

Today, there are dozens of BI tools available. To determine the top five, these were the most commonly cited among ten websites that ranked the best BI tools. These five BI tools are not ranked in any particular order.

1. Microsoft Power BI

One of the most popular BI tools is Power BI, offered by leading software giant Microsoft. This tool is downloadable software, so you can choose to run analytics either on the cloud or in a reporting server. Syncing with sources such as Facebook, Oracle, and more, generate reports and dashboards in minutes with this interactive tool. It comes with built-in AI capabilities, Excel integration, and data connectors, and offers end-to-end data encryption and real-time access monitoring.

Learn Power BI with Coursera: In just two hours, you can learn the basics of Power BI Desktop with this guided project. You’ll load and transform data to create interactive reports and dashboards. 

2. Tableau

Tableau is known for its user-friendly data visualization capabilities, but it can do more than make pretty charts. Their offering includes live visual analytics, an interface that allows users to drag and drop buttons to spot trends in data quickly. The tool supports data sources such as Microsoft Excel, Box, PDF files, Google Analytics, and more. Its versatility extends to being able to connect with most databases.

Learn Tableau with Coursera: There are several options for learning how to use Tableau.

3. QlikSense

QlikSense is a BI tool that emphasizes a self-service approach, meaning that it supports a wide range of analytics use cases, from guided apps and dashboards to custom and embedded analytics. It offers a user-friendly interface optimized for touchscreens, sophisticated AI, and high-performance cloud platforms. Its associative exploration capability, Search & Conversational Analytics, allows users to ask questions and uncover insights intuitively, which helps increase data literacy for those new to using BI tools.

4. Dundas BI

Dundas BI is a browser-based BI tool that’s been around for 25 years. Like Tableau, Dundas BI features a drag and drop function that allows users to analyze data on their own, without involving their IT team. The tool is known for its simplicity and flexibility through interactive dashboards, reports, and visual analytics. Since its inception as a data visualization tool in 1992, it has evolved into an end-to-end analytics platform that is able to compete with the new BI tools available today.

5. Sisense

Sisense is a user-friendly BI tool that focuses on being simplified and streamlined. With this tool, you can export data from sources like Google Analytics, Salesforce, and more. Its in-chip technology allows for faster data processing compared to other tools. Its main features are the ability to embed white label analytics, meaning a company can fully customize the services to its needs. Like others, it has a drag-and-drop feature. Sisense allows you to share reports and dashboards with your team members as well as externally.

Other popular BI tools include: Zoho Analytics, Oracle BI, SAS Visual Analytics, Domo, Datapine, Yellowfin BI, Looker, SAP Business Objects, Clear Analytics, Board, MicroStrategy, IBM Cognos Analytics, Tibco Spotfire, BIRT, Intercom, Google Data Studio, and HubSpot.

List BI tools on your resume

You can get familiar with one or more BI tools by learning independently or on the job. Many top companies use them, so you can benefit from listing the most common ones in the skills section of your resume if it makes sense for the role and industry in which you’re applying. Hiring managers may specifically keep an eye out for applicants who have experience with specific BI tools, especially if it is referenced in the job description.

Explore business intelligence with Coursera

Dive into Business Intelligence Concepts, Tools, and Applications to learn how to work with large data sets using MicroStrategy’s Online Analytical Processing and Visualization capabilities to create visualizations and dashboards. These skills can be used to support strategic decision-making across any business sector.

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Article sources

1. BARC. “The Benefits of Business Intelligence... Why Do Organizations Need BI?, https://bi-survey.com/benefits-business-intelligence.” Accessed April 13, 2022.

Written by Coursera • Updated on

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