Best Business Intelligence Tools or Top BI Tools: There are several tools and skills accessible to acquire and master in today’s fast-changing world. Business intelligence and information management are two of the most critical business skills in today’s digital and data-driven world. Nowadays, business intelligence may be seen as a critical corporate capability. By enhancing brand recognition, employee engagement, and profitability, BI may help enterprises stay ahead of the competition.
Businesses that employ BI analytics are five times more likely to make faster, more informed choices. In this instance, it is critical to have Business Intelligence skills. This article will summarise the most widely used BI tools. Several BI tools are available today, but I’ve compiled a list of the 13 best and most used business intelligence tools.
The 13 Best Business Intelligence Tools (Top BI Tools)
Following is a list of the 13 best business intelligence tools or top BI tools.
1. Google Data Studio
Google Data Studio is a free web-based tool that was created in 2016. On the other hand, Google’s straightforward, user-friendly design for providing business intelligence may be its most compelling selling feature. This tool performs well when used with Google data sources such as Google Analytics, Search Console, and YouTube analytics. A Google Sheet may be used to extract any data you want. However, having many pre-built connections that may be used to get data from other sources is not particularly helpful. In addition, it’s not easy to operate with a variety of data kinds.
The Data Studio has a lot of analysis and visualization tools, which gives it a significant edge over competing analytics suites. However, Data Studio is web-based might be a disadvantage. It’s easy if you’re willing to share. You will, however, be unable to export to PDF or other commonly used formats. In addition, automated report distribution is restricted.
2. Yellowfin BI
Yellowfin BI (Business Intelligence) is a business intelligence tool and ‘end-to-end’ analytics platform that integrates visualization, machine learning, and collaboration. You can sift through large amounts of data using straightforward filters (e.g., checkboxes and radio buttons) and browse dashboards from almost anywhere (due to this tool’s accessible flexibility) (mobile, webpage, etc.). The wonderful thing about this BI tool is that it enables you to advance dashboards and visualizations via a no-code/low-code development environment.
3. IBM Cognos Analytics
Cognos Analytics, IBM’s flagship business intelligence suite, is a cloud-based analytics and business intelligence platform. It can import data from a variety of sources and generate interactive dashboards, visualizations, and reports. Users vary in size from tiny companies to huge organizations across numerous sectors. IBM touts Cognos Analytics as an artificial intelligence-enhanced decision-making tool. This platform is unusual because it allows users to browse charts and subscribe to alerts. You get real-time updates.
4. Looker
I was unaware that Looker was a BI tool until I discovered three full-time Data Analyst openings at Disney, Warner Media, and a local startup that needed skill in Looker. So when I initially looked at Looker, it had to be on my list of BI tools I wanted to learn. Looker is a web-based business intelligence platform. It’s simple to use, easy, and adaptable.
You may construct dynamic visualizations by including a range of graphs and charts. Tableau and Looker have several similarities. The most appealing feature of Looker is its drag-and-drop dashboard building. This would be advantageous for non-technical users. Visualizations and reports are accessible from any device. They may be exported from the Looker dashboard for cooperation with other users.
5. MicroStrategy
MicroStrategy is a business intelligence tool for enterprises that enables strong (and fast) dashboarding and data analytics and cloud solutions, and hyperintelligence. Users may use this solution to spot trends, uncover new possibilities, and boost productivity, among other things. Users may connect to one or more sources, regardless of whether the incoming data comes from a spreadsheet, the cloud, or business data tools. It is accessible through PC or mobile. However, the setup might need numerous individuals and a fair amount of understanding of the app to get started.
6. Microsoft Power BI
Power BI, Microsoft’s most popular business intelligence tool, is designed for use by business analysts and data scientists. I first encountered Power BI while interning at Larsen & Toubro in 2017. Power BI is utilized for welding and arching shifts to assess revenue expenditures across departments, employee productivity, and real-time data processing.
The PowerBI is easy to use and has a drag-and-drop interface. This creates a sense of familiarity or likeness for MS Excel users. Power BI is a self-service platform that requires no programming. This is most likely why it has been so successful. PowerBI provides a comprehensive set of connectors for connecting to Azure.
Why Power BI? by Microsoft outlines and reasons why PowerBI is a de facto standard for Data Scientists. Power BI connects to, models, and visualizes data. It generates memorable reports that are personalized to your brand KPIs. However, I’ve found that PowerBI slows significantly when dealing with enormous data sets. If your data set is huge, you may want to examine other methods.
7. Qlik and QlikSense
Line charts, pivot tables, pie charts, and bar charts are all examples of QlikView. It is extensively utilized across many industries. QlikView is another tool for Business Intelligence and Data Discovery. The objective is to provide guided analytical apps and dashboards for various business problems. This software enables users to get insights into data and establish links between numerous factors. QlikView’s popularity has sparked much debate. QlikView is a less expensive alternative to Tableau, which is well-known. It uses an in-memory paradigm that enables the precise manipulation of massive data sets.
8. Datapine
The Datapine is a comprehensive business intelligence platform that simplifies even the most complicated data analytics processes for non-technical users. Datapine’s solution enables data analysts and business users to effortlessly combine disparate data sources, conduct advanced data analysis, create interactive business dashboards, and provide actionable business insights thanks to a full self-service analytics strategy.
9. SAP HANA
The SAP HANA (High-Performance Analytic Appliance) is an RDBMS (Relational Database Management System) created by SAP. It is typically used as a database server, storing and retrieving data required by apps. SAP HANA is an ETL-based replication solution that leverages SAP Data Services to move data from non-SAP sources to the SAP HANA database. SAP HANA enables SAP-based organizations to handle massive volumes of real-time data rapidly. Because SAP is a closed-source environment, HANA may not be a viable choice for data scientists, but it may be beneficial for companies and professions inside SAP.
10. SAS
SAS, like R, is a statistical programming tool that enables complicated statistical calculations and advanced data analysis. It is a proprietary closed-source tool that enables the execution of complex modeling tasks. SAS is a dependable tool that experts and big enterprises use. It is not ideal for novice data scientists, but it may be used to get started. SAS is the market leader in enterprise analytics, without a doubt. On the other hand, its capabilities may be less striking than those of R or Python. SAS may be challenging to use for modeling and visualizing data. The learning curve may be difficult and even unpleasant for huge organizations with enormous expenditures.
11. Zoho Analytics
Zoho is a cloud-based online workspace that includes Zoho Analytics, a self-service business intelligence platform. It is a cloud-based platform that is also available for on-premise installation. Zoho may acquire data from a variety of sources. Zoho can integrate data seamlessly from major business software and self-service tools. The data is stored at a data center in the United States. Zoho Analytics is used by more than 500 000 enterprises and has about 2 million users and 50 million reports. According to my study, Zoho Analytics has the most robust 3rd-party connector ecosystem – 500+ connections for business apps. So this is a good tool to investigate.
12. Tableau
Tableau is a well-known data visualization tool often used in Business Intelligence. It accelerates and ensures the reliability of data analytics. In addition, the visualization dashboards and spreadsheets in Tableau make it simple to simplify and clean up raw data. For years, large corporations such as Verizon, Charles Schwab, and Coca-Cola have relied on Tableau to make educated choices. Well, anyone interested in a data science or data analytics tool should be familiar with Tableau.
13. TIBCO Spotfire
In 2007, TIBCO (Wikipedia) bought Spotfire, a business intelligence startup in Somerville, Massachusetts. Spotfire is a general-purpose visualization tool similar to Tableau and QlikView. Tableau Public and Power BI Desktop are both available free of charge. On the other hand, TIBCO Spotfire is priced at $650.00 per user per year. Independent Data Scientists may object to the lack of a free edition. This story study demonstrates how Accor Hotels used TIBCO Spitfire to enhance the client experience and integrate quickly, easily, and simply. TIBCO was the pioneer in analytics and integration. Unfortunately, Spotfire was also contained inside the cat.
Conclusion: Business Intelligence Tools
This concludes my article. I value your time! I hope you found this information helpful. Kindly indicate which BI tool is most critical to you.
