Top Data Analytics Tools for Business

Table of Contents

The entire world is surrounded by data. Thanks to the tremendous digital influence, everything from entertainment to profession to personal info, involves data. Ever wondered how so much content gets processed through various data analytics tools and how does it reach the audience? It’s mind-boggling, isn’t it? It is Data Analysts who work on the background to ensure that data is filtered and it reaches the right audience.

So today we chalk out some of the most popular and frequently used tools by the Analysts. Let’s understand the process of data analysis. The below flow chart gives you the simplest definition of Data Analysis.

Hope that was simple! Though the process looks simple, there is a lot of effort that goes into getting the right data to the right people. But how does this happen? Kudos to Data Analysts and the tools/software available today that make the life of organizations easy. With a plethora of options available today, there is always a challenge to identify the right tool which is easy to use and gives us accurate results. How to choose the right tool? Choose the tool by checking the “OTP” box:

  • Outline the goal of an organization
  • Type & Format in which you need the data
  • Pricing of the software; there are open to use options as well as paid options available


Through this blog we help you with some of the most preferred tools that is the ‘astra’ for data analysts.

  • MICROSOFT POWER BI: Microsoft Power BI has the ability to import data from various sources in varied formats. It offers the advantage of personalized dashboards, and data mining. For a more complex task the user must have knowledge of other tools like Power Pivot. It can also be used as a collaborative data visualization tool.
  • R PROGRAMMING: This is one of the most widely used tools across industries. It is used for statistics and data modeling. R programming runs on a variety of platforms like UNIX, Windows and MacSOS. Empowered with 11,556 packages, you can browse it as per category. It helps you to automatically install packages as per the requirement, which can be assembled with Big Data.
  • PYTHON: An object oriented scripting language that is easy to read, write and maintain. This is a free open resource tool. This is compatible with functional as well as structures programming methods. Similar to JavaScript, Python is very east to learn and is user friendly. The best feature is that it can be assembled on SQL server, a MongoDB or JSON. It helps in smooth management of text data

  • SAS: One of the leaders in data analytics, SAS is a programing environment and language for data manipulation and a leader in analytics. It is easily accessible, manageable and has the ability to access data from any of the sources. The products introduced by SAS in 2011 have helped in attaining customer intelligence and its various modules have facilitated profiling of customers for web, social media and marketing analytics.
  • EXCEL: This one needs no introduction. The most popular and widely used tools by every organization. Even if you are an expert in other tools, Excel is always needed when it comes to analysis of clients internal data. It helps in the analysis of complex task that summarizes data with preview of pivot tables that is crucial for filtering of data.
  • QlikView: With unique features like patented technology and in-memory data processing that delivers faster results. It also stores the data in the results. The data is automatically maintained and it can be compressed upto 10% from its original size. The visualization can be done by using colors i.e. related and non-related data can be differentiated by assigning colors.

These tools are a boon to any organization as it helps in forecasting the future with valuable data and helps a firm in reducing the risks. Therefore be wise in investing in the right resources.

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