Top 10 Business Analytics Tools Used by Big Tech Companies

The article lists some of the trending business analytics tools used by big tech for smart analysis

Business analytics tools are software programs that are used to gather, arrange, visualize, and analyze data gathered from business operations in order to identify trends and patterns and support decision-making based on actionable facts. The amount of data that these cloud applications create today—from SLM (Service Life-Cycle Management) to SCM (Supply Chain Management), ERP (Enterprise Resource Planning), and CRM (Customer Relationship Management)—is daunting, and it is growing at an astounding rate and that has created the need of some top business analytics tools. Undoubtedly, this scenario has made business analytics an excellent career to opt for. They use business analytics tools to review and analyze data to enable smarter decision-making. There are many emerging business analytics tools used by big tech and start-ups from all over the world to provide seamless analytics solutions to assist enterprises in gaining actionable insights from the data they collect. Here we will see the top 10 business analytics tools used by big tech to be more efficient, optimize and automate their processes, and also focus on their revenues and growth.


Splunk is one of the most widely used business analytics tools in small and medium-scale industries. Splunk was first introduced to handle data from machine log files, but it has since gained a wide range of advanced capabilities, such as an intuitive online interface and a number of visualization options.


One of the most widely used business analyst software packages, Sisense, includes powerful and dynamic text analysis functionalities that let users turn unstructured text into insightful business data. The Sisense business analytics platform leverages open-source language for computational statistics and includes the exclusive Sisense Crowd Accelerated BI. Users may do in-depth analysis and visualization of complicated data, which encourages data-driven decisions and enhances trend forecasting.


The ground-breaking KNIME business analytics tool was created in 2004 by a group of highly skilled software engineers from the University of Konstanz in Baden-Württemberg, Germany. One of the best high-performance business analyst tools available, KNIME enables a variety of machine learning and data mining components that support persistent analysis, visual programming, and seamless business analytics reports with its novel data-pipelining approach.

Dundas BI

The R programming language is used to provide world-class business analytics and business intelligence solutions by the fully-equipped Dundas BI. Dundas BI’s sophisticated business analytics tool offers automated analytics, trend forecasting, and a high-level dashboard that enables users to easily drag and drop features to display data and produce business analytics reports.

TIBCO Spotfire

One of the most cutting-edge business analytics tools, TIBCO Spotfire provides strong and automated analytics solutions that let data professionals perform business analytics reports and analyses over a predetermined time period. With the most recent Spotfire platform upgrade, TIBCO’s scalability, statistical analysis tools, and ability to analyze text-based unstructured data have all greatly enhanced.


One of the most popular data analytics tools, Microsoft Excel, gives users choices like sharing workbooks, working with the most recent version for real-time collaboration, and directly downloading data from a picture to Excel, among others. Microsoft Excel is used daily by almost all businesses to extract useful information from the data.

Power BI

Power BI is one of the top business analytics tools produced by Microsoft. End users can independently construct dashboards and reports using the self-service business intelligence elements it offers together with dynamic visualizations. 

Apache Spark

Big data analytics, often known as large-scale data analysis, maybe the primary purpose for why Apache Spark was created as a data processing engine. Because it can run on a variety of platforms, like Hadoop, Apache Mesos, or Kubernetes, it is an incredibly flexible analytics option. It is also recognized for being extremely speedy and developer-friendly thanks to its in-memory data engine. For data scientists and engineers working on enterprise-scale analytics, this platform is intended. 


The Domo Business Cloud, a low-code data app platform, enhances the potential of business intelligence by aggregating all of your data and putting it to use across any business process or workflow.


A data science platform called RapidMiner may have been developed for companies to look at the combined impact of an organization’s employees, knowledge, and data. The Rapid Miner info science platform is intended to support various analytics users over the whole AI lifecycle.

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