From SLM (Service Life-Cycle Management) to SCM (Supply Chain Management) and ERP (Enterprise Resource Planning) to CRM (Customer Relationship Management), the volume of data that these cloud applications generate today is overwhelming and accelerating at a phenomenal rate. To help organizations extract actionable insights from the data they generate, recognized technology companies and startups worldwide are creating business analysis tools and techniques that deliver seamless analytics solutions.

Packed with powerful features, today's state-of-the-art analytical tools for business facilitate efficient data collection, analysis, and presentation in real time, empowering enterprises to identify trends/patterns in vast datasets and create new business analytics models. Check out this video about business analytics tools in 2025. How many of these do you know how to use?

What Are Business Analytics Tools?

Business analysts use various application software to capture quantitative and qualitative data from different business systems and incorporate it into a repository. Analysts then review and analyze the data to enable smarter decision-making.

Most companies deploy a mix of business analytics software, including statistical tools, predictive modeling, and data mining tools. These software applications for business analytics provide organizations with a holistic overview of key insights that improve efficiency, productivity, and profitability.

Difference Between Business Analytics and Business Intelligence Solutions

Although Business Intelligence (BI) tools also compile and analyze data, software for business analytics takes a deeper dive, helping to identify weaknesses, alert policymakers to unanticipated events, fix potential problems, and even forecast future performances.

High-caliber tools business analysts use for requirement gathering provide the knowledge and confidence enterprises need to improve customer satisfaction, increase their competitive edge, and attain business goals.

The popularity and demand for premium-quality business analytics tools are at an all-time high because of the rich functionalities these advanced business analytics software deliver regarding business success and future growth. According to experts, the growing relevance of data analysis will drive improved business decisions and create new job openings in multiple fields. Below are the top ten most widely used business analytics tools and solutions designed for modern enterprises.

1. SAS Business Analytics (SAS BA)

The high-grade text analytics capabilities of the SAS-based business analytics software allow users to inspect and transform unorganized text data into relevant information that analysts can explore to discover meaningful insights.

SAS BA is fully loaded with a range of statistical tools, simplifying the process of analyzing large data sets in real time. The top-of-the-line business analytics platform also predicts future trends from the information harvested from big data.

2. QlikView

QlikView is one of the most preferred tools for business analytics because of its unique features, such as patented technology and in-memory processing, which facilitate the delivery of ultra-fast business analytics reports.

Included among the best business analyst tools, QlikView allows users to visualize data relationships using specific colors for related and non-related data with automatically maintained data associations. It is compressed to 10 percent of its native size.

3. Board

Board features in the list of top-rated business analyst software tools because of its industry-leading business analytics model that permits users to create interactive and intuitive business analytics reports and dashboards.

The highly scalable business analytics platform integrates the best-in-class analytical tools for business, including a powerful statistics suite.

The Board business analytics tool can manage massive data volumes. It can also support accurate scenario analysis and forecasting by manipulating the data supplied to scenarios.

4. Splunk

Splunk is one of the most widely used business analytics tools in small and medium-scale industries.

Initially launched to process machine log file data, Splunk has added many sophisticated features, including a user-friendly web interface and visualization options.

5. Sisense

Sisense - one of the most popular business analyst software tools - incorporates dynamic and robust text analysis functionalities that enable users to transform unstructured text into valuable business intelligence.

The Sisense business analytics platform, which features the proprietary Sisense Crowd Accelerated BI, uses open-source language for computational statistics. It allows users to perform extensive analysis and visualization of complex data, which promotes data-driven decisions and improved forecasting of future trends.  

6. Microstrategy

The Microstrategy business analytics software integrates superior analytics capabilities that allow hassle-free processing of unstructured text data, which specialists can further analyze via the platform's text analytics solutions.

One of the most up-to-date business analytics tools, Microstrategy, incorporates insightful analytical and statistical capabilities that enable real-time trend forecasting with options for third-party data mining.

The first-rate business analytics tools combine a range of business analysis tools and techniques, allowing users to create and share business analytics reports from anywhere and on any device.

7. KNIME

In 2004, a team of expert software engineers from the University of Konstanz in Baden-Württemberg, Germany, developed the innovative KNIME business analytics platform.

Renowned as one of the best high-performance business analyst software, KNIME, via its unique data-pipelining approach, facilitates varied machine learning and data mining components that support persistent analysis, visual programming, and seamless business analytics reports.  

8. Dundas BI

The fully-equipped Dundas BI offers first-class business analytics and business intelligence solutions using the R programming language.

With robust business analytics tools, Dundas BI provides automated analytics, trend forecasting, and a high-level dashboard that helps users visualize data and create business analytics reports through easy-to-use drag-and-drop features.

9. TIBCO Spotfire

TIBCO Spotfire is one of the most advanced tools for business analytics. It offers powerful and automated analytics solutions that allow data professionals to run business analytics reports and analyses over a defined time span.

The latest upgrade of the Spotfire platform has significantly improved TIBCO's scalability, statistical analysis capabilities, and capacity to analyze text-based unstructured data.

10. Tableau Big Data Analytics

Experts agree that Tableau is one of the best business analyst software, given its dynamic and cutting-edge capabilities for unstructured text analysis.  

Tableau's business analytics platform, which includes robust and reliable statistical tools, empowers users to perform in-depth analyses of social media networks and predict patterns based on current and historical data. 

11. Excel

Microsoft Excel, one of the most widely used tools for data analytics, offers users options like sharing workbooks, using the most recent version for real-time collaboration, and uploading data directly from a photograph to Excel.

Almost all businesses use Microsoft Excel daily to glean actionable insights from the data. Here are some recent improvements to the Windows platform:

  • Workbook Statistics allow you to take a snapshot of your workbook.
  • You may add backgrounds and premium stock photos to your documents for free to offer them flair.

12. Power BI

Microsoft makes Power BI among the many business analytics tools. It offers dynamic visualizations with self-service business intelligence features, allowing end users to create dashboards and reports independently without assistance. 

13. Domo

The Domo Business Cloud, a low-code data app platform, expands business intelligence capabilities by combining all of your data and using it across any business process or workflow. 

14. RapidMiner

RapidMiner may be a data science platform created for businesses that examine the influence of an organization's workers, knowledge, and data taken as an entire. The info science platform from Rapid Miner is designed to assist numerous analytics users across a comprehensive AI lifecycle. 

15. R and Python

R and Python are the two most popular programming languages in the data analytics industry. Python may be a high-level, elaborated language with dynamic semantics and easy syntax, whereas R is an open-source program used for analytics and statistics.

16. Apache Spark

Apache Spark may be a data processing engine designed primarily for big data analytics, often called large-scale data analysis. It's a remarkably flexible analytics choice because it can function on various platforms, like Hadoop, Apache Mesos, or Kubernetes. In addition, due to its in-memory data engine, it's renowned for being developer-friendly and highly quick.

This platform is meant for data scientists and engineers working on enterprise-scale analytics. Spark is suitable for several use cases, including managing real-time data streams and training machine learning algorithms, because of its flexibility and petabyte-scale processing capability.

17. Apache Storm 

The Clojure programming language usually creates a distributed stream processing computation system called Apache Storm. Nathan Marz initially developed the project and, therefore, the BackType team. Then, after being purchased by Twitter, it was made open source.

A system for networked real-time computation called Apache Storm is free and open source. It is easy to use, compatible with any computer-oriented language, and fun to use Apache Storm!

18. PIG and HIVE

Yahoo had difficulties processing and interpreting massive datasets due to this. Apache Pig was created to research massive datasets without utilizing time-consuming and difficult Java scripts. The Pig was specifically designed for non-programmers.

Because Facebook uses Hadoop to manage Big Data, Facebook actively contributed to the creation of Hive. Hadoop processes data using MapReduce. In the past, users had to make lengthy, intricate scripts to process and evaluate data. Moreover, nobody was an expert in Java or other sophisticated programming languages. On the other hand, many of us were at ease creating SQL queries. This necessitated creating a language like SQL, which was well-known to all or any users.

While PIG facilitates operations with large amounts of knowledge, Hive command language (HiveQL) is tailored to the unique needs of analytics. PIG was created as an abstraction to urge around Java's convoluted syntax for MapReduce. HIVE, QL, conversely, is predicated on SQL, making it simpler to find out for individuals who already know SQL. In addition, PIG supports AVRO, speeding up serialization.

Career Options in Business Analytics

Since the beginning of the 21st century, a variety of new career options and employment paths have emerged. However, no career choice can match Business Analytics regarding salaries, learning, and training opportunities in everyday work.

With businesses increasingly leveraging business analytics tools, multiple avenues open for qualified business analysts in diverse sectors, including automotive, healthcare, retail, banking, hospitality, and aviation.

Depending on your skills and interests, you may specialize in a business analyst role, such as Big Data Engineer, Data Scientist, Database Administrator, Marketing Analytics Manager, or Data Visualization Specialist.

But How Do You Start Your Career and Land a High-Paying Job?

The key to starting your career as a business analyst is to acquire the right skill sets. You can explore and enroll in Simplilearn's innovative, interactive, and career-focused Post Graduate Program In Business Analysis - access to masterclasss from IBM and Purdue University, Live Sessions by top Business Analyst experts, and more. Start today!

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