What are the Top Tools for Data Analysis?

To solve data analysis problems, you need to have powerful tools that are easy to use and preferably free, in order to assist you in analyzing and visualizing the data. Fortunately, there is a number of significantly powerful tools in analytics that are open sources and free to help improve the work in business and develop proficiency in your future career. Due to the high price of the well-known tool SAS in data analytics, some small and medium corporations cannot afford it. That’s why they use other free tools and programs to analyze their data instead of investing in a tool that does not match their analysis needs. Here are some open source analytics tools:

·      Hive and PIG: both languages are SQL and are integral tools that helps decrease the complications of writing a map queries. A huge number of companies use these tools.

·      R : the most popular tool in the analytics industry because it deals with large data much better than it used to do in the past. It surprisingly exceeded SAS in the usage of data and became the choice for companies due to the higher price of SAS. In addition to that, this tool also merge with big data platforms very well and that participated in its success.

·      Python: the favorite tool for data scientists and programmers is python due to its simplicity, easy language, and it is also fast. Recently, it also became capable of covering mathematical and statistical functions.

·      Apache Storm: this is the suitable and perfect tool when using moving data that continues to come like a streaming process.

·      Apache Spark: this tool is used for the tremendous volume of data, and it has its own machine learning library for analytics.

And now, here are some commercial analytics tools: these tools are paid not free.

·      SAS: it is the most tool used in analytics. It added a lot of new modules and made it easier to learn such as SAS Analytics Pro for Midsize Business, SAS Anti-Money Laundering and SAS for IOT. The high price of SAS is being reduced for more flexibility.

·      Tableau: it is an easy tool to learn in order to analyze the data and demonstrate visualization and dashboards in a simple way. It handles much more data than Excel and creates visualizations better as well. Even though there are better alternatives, Tableau is distinguished by offering a free trail.

·      Excel: it is the most tool used worldwide. All data scientists have to use this tool whether a professional or a beginner. Most non-professional will not necessary use SAS but everyone does excel.

·      Google Search Operators: this tool authorizes you to filter Google results and allocate the most beneficial result that is relevant.  

·      Qlik View: similar to Tableau, this tool is one of the top tools for data visualization. However, it is more flexible and slightly faster than Tableau but on the other hand, Tableau is easier to learn.

·      Solver: an optimization tool that also offers linear programming in excel that helps put bands. It solves a problem in a short time compared to others.

·      wolframAlpha: it is a search engine that is hidden and helps to support Apple’s Siri. It illustrates graphs and charts with detailed information and responses.

·      NodeXL: it is an analysis and visualization software that consists of relationships and network. NodeXL takes the large friendship map located on Facebook and LinkedIn, and explains it better by providing perfect calculations.  

Those open sourced and commercial analytics tools are a group of a bigger collection. It is a big challenge to gather big data and analyze it, but with these different tools, most businesses are capable of handling an enormous amount of data.
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Resources:

http://www.kdnuggets.com/2014/06/top-10-data-analysis-tools-business.html

http://analyticstraining.com/2011/10-most-popular-analytic-tools-in-business/