Top 10 Business Analytics Tools For Business

Any Organization putting their services across to their customers wants to improve and improvise themselves so that they give the best of their services to the Customers. This is a continuous process from any of the Organization’s points of view. In addition to that, with the changing society and factors governing it – the requirements of the customers change too which need to be accounted for by service-providing organizations too.

To be able to do that, each of the Organizations should be able to pull themselves up to a position where they can innovate on the existing solutions and make it a better one for the customers to rely upon. This will not only help Organization to retain the existing customers but also attracts newer ones too.

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Let us now take a look at the top 10 business analytics solutions/tools available for businesses to opt on:

List of Top 10 Business Analytics Tools 

What Are Business Analytics Tools?

Let us take a look at the most recent additions to the realm of Business Analytics first and then we will take it further with the commercial business analytics tools available for businesses to work with:

Here, the Most Popular 5 Open source Analytics tools:

1. R:

R is the latest trend that has been introduced into the realm of Business Analytics. This has also been observed to surpass the usage of one of the commercial business analytics tools SAS, even though it is a cost-effective solution. R has grown more versatile and improved over the years and has got a nice facelift after Microsoft took over from its earlier counterparts.

Over the last couple of years, there are more than 1800 models added to R and making its available count of models for usage at an enormous figure of 8000. The count has added a lot of capabilities set to R and also provides seamless integration with Big Data which has proven of great success over the years now.

2. Python:

Python has been the recent favorite for programmers all over the world, as it has gained more importance with the advent of Big Data. Python’s seamless integration with Big Data is also another reason why it gaining such importance over the years. With the development of analytical and statistical libraries likes numpy and scipy, Python has grown into a more powerful analytics tool.

Increasingly, this has turned into a favorable language for the programmers with its easy-to-use syntax and simplicity in learning. Folks who are already familiar with Python have picked it up as a tool of choice in accessing Big Data.

3. Apache Spark:

Apache Spark is yet another open-source processing engine that is built with its focus on analytics (on unstructured data). The most reliable reason for it gaining importance is that has a very easy process of integration with the Hadoop ecosystem. With its own Machine learning library, Apache Spark has also been marked as an ideal option for Business Analytics.

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4. Apache Storm:

Apache Storm is another Big Data tool of choice in moving data when it comes to a continuous stream. Apache Spark is an ideal solution for static data whereas Apache Storm is best suited for real-time analytics and stream processing.

5. PIG and HIVE:

Pig and Hive are the internals of the Hadoop ecosystem which allows reducing the complexity of MapReduce queries to a bare minimum. Hive more so than Pig is more like SQL and these find its usage in Organizations that want to leverage the Hadoop ecosystem and in turn work with Big Data.

Until now what we have seen are all open source solutions and tools. Now let us take a look at the top 5 Commercial Business Analytics tools which comes with an additional cost to this component for your Organization, as below:

Top 5 Commercial Business Analytics Tools:

1. SAS:

SAS finds its usage very wide in the analytics industry and also is a viable option over the rest of the business analytics solutions. It is a robust, easy to learn, and versatile tool. Over the years, SAS has added more and more modules to gain the best use for SAS analytics for IoT, SAS anti-money laundering, SAS analytics pro.

2. Tableau:

Tableau is a super easy to learn tool which does the analytics job of slicing, dicing your data, and create wonderful visualizations, dashboards in Tableau. Visualizations are better over Excel and definitely can handle loads of data than excel can.


Excel is one of the cheapest and most widely used analytics tools all over the world. Whether or not you are an expert in any of the other Business Analytics tools like R or Tableau, you will definitely find most of the work being done on Excel firstly. Professionals with no business analytics background will definitely rely on tools like SAS or R but everyone has Excel.

4. QlikView:

QlikView along with Tableau occupy the first spot on any of the Data Visualization studies. QlikView in this context is faster in response than Tableau and gives a lot of flexibility for the experienced users.

5. Splunk:

Splunk is yet another popular business analytics tools when names like Cloudera or Hortonworks are considered. Splunk was first made with the intention to process machine log files data. Splunk has added a lot of visualization options and made its web interface more user-friendly to improve its usage.


In today’s world, business decisions have taken a radical shift from then Just guesses to well thought about decisions. Gone are those days where Organizations used to take decisions on various kinds of guesses and rumors and expected those to work towards the betterment of the Organization.  

Hence the Organizations are given the choice to choose amongst the open-source and commercial business analytics solutions and tools to make the best use of them for them to take the best possible decisions.


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Last updated: 03 Apr 2023
About Author

Ravindra Savaram is a Technical Lead at His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.

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