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The increasing importance and demand for data analytics have opened up new potential in the market. Each year, new tools and programming languages are being launched aimed at easing up the process of analyzing and visualizing the data.

While many such advanced business intelligence tools come up in paid versions, there are great free and open-source data analytics courses and tools available in the market too. Read on to find out about the 10 best and most popular data analytics tool for business right now.

1. R Programming
R is the most popular programming language cum tool widely used by experts for the purpose of data analytics and visualization. The tool is free and open-source in nature and allows the users to alter its code set for clearing bugs and updating the software on their own.
2. PYTHON
Python is an open-source and free OOP based scripting language popular in the data analytics market since the start of the 90s. Python supports both structured and functional programming methods and is very easy to learn and operate upon. Python is expert in handling text-based data.
3. Tableau Public
Tableau Public is another free software and business intelligence tool which is capable of connecting all kinds of data source be it Excel-based data, Data Warehouse or web-based data. Tableau creates maps, graphs and dashboards with real-time updates presenting on the web. The data can be shared over social networks too.
4. SAS
Sas is a leading analytics tool and programming language specifically developed for the purpose of interacting with and manipulating data by the SAS institute in 1966 with updates presented during the 80s and 90s. Data present in SAS can be accessed, analyzed and managed easily from any sources and is capable of predicting behaviors of customers and prospects along with recommending optimized communication models.
5. Excel
One of the most popular and underrated data analytics and visualization tool in the market, Excel was developed by Microsoft as part of their MS Office and is one of the most widely used tools in the industry. All kinds of data analytics tools still require Excel to work in some kind of way and it is very easy to be learnt and operated.
6. KNIME
KNIME is a leading open source and integrated analytics tool developed by a team of software engineers from the University of Konstanz in January 2004. KNIME allows the users to analyze and model the data through visual programming integrating components of data mining and machine learning via its modular data pipelining concept.
7. Apache Spark
Developed in 2006 by the Berkeley’s AMP Lab of University of California, Apache is a fast large-scale data processing, analysis, and visualization tool capable of executing applications around 100 times faster in memory and 10 times faster on disk. It is popular for data pipelining and machine learning models development allowing it to double up as business intelligence tool.
8. RapidMiner
RapidMiner is another powerful data analytics tool which can double up as business intelligence tool owing to its capability to perform predictive analysis, behavioral analysis, data mining, etc. The tool can incorporate with any other data source types such as Excel, Microsoft SQL, ACCESS, Oracle, Ingres, IBM SPSS, Dbase, etc.
9. Google Analytics
A freemium and widely recommended product for data analytics, Google Analytics is a perfect offering from Google for the Small and Medium-scale enterprises who don’t possess the technical knowledge or the means to gather that knowledge in the present course.
10. Splunk
Splunk is an analytics tool mostly directed to searching and analyzing machine-generated data. The tool pulls up all text-based log data and provides the means to search through it for gathering any relevant or required data.

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