Big Data Analytical Tools for Researchers
                     Big Data Analytical 
Tools for Researchers
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Big data analytics is the process used for interpreting large data which 
includes market trends, hidden patterns, customer requirements and other 
details which deems useful for organizations to make clear business 
decisions. The term used for the collection of large data sets that are very 
huge and complex is called big data. 
This type of data is often difficult to process. The use of traditional tools or 
applications is not possible with big data. The size of this data exceeds in 
Petabytes. Since this type of data has a huge variety, it brings multiple 
challenges in reference to its complexity and volume that is associated with 
big data types. According to recent surveys, it is observed that nearly 80% of 
the data that is created is available in an unstructured way. 
Some of the good tools for big data analytics are as follows:
MongoDB
One of the most popular open-source cross-platform sources that utilizes a document-
oriented program. It makes use of JSON-documents along with schemas that make it a 
prominent data analytics tool
Apache Hadoop
It is an open-source platform that helps in the distribution and storage of large data. It is 
more based on computer clusters which are constructed on commodity hardware. Apache 
Hadoop is free software with framework based on Java. This tool can help store a very large 
amount of data in the form of a cluster.
Tableau Public
This tool offers a larger insight into the hypothesis generated. The USP of this tool is one 
doesn’t require any programming skills and can publish the same on the web for free. 
Moreover, the visuals can be embedded into blogs and shared on social media.
Limitation:
• Require Excel or .txt to read the document.
• There is a limitation to data size.
• All information is public offers a little scope of privacy.
KNIME
These big data analytics tools help in analyzing and manipulating the information through 
the use of visual programming. It is also used for integrating data mining and AI as it 
supports all types of programming language. Furthermore, one needs no write blocks or 
codes. You can instead drop and drag connection points in between the activities. 
However, this tool renders poor data visualization.
NodeXL
This is a free open-source network analysis and visualization software tool. It is 
considered the best data analytics tool that includes advanced network metrics, renders 
access to social media and supports automation. It’s easy to import data, analyze and 
visualize graph which can be integrated into Microsoft Excel 07 to 16 models.
Microsoft HDInsight
Microsoft HDInsight is a big data solution provided by Microsoft and powered by Apache 
Hadoop. This is available as a service in the cloud. The HDInsight makes use of Windows 
Azure Blob storage as its default file system. It helps to provide high availability at low cost.
NoSQL
The use of traditional SQL is traditionally opted to handle large amount of structured data. 
On the other hand, the NoSQL (Not Only SQL) is needed to handle unstructured data. 
NoSQL databases are used to store unstructured data which have no particular scheme. 
There are multiple open-source NoSQL DBs which are available to analyze the Big Data.
Hive
Hive is a distributed data management for Hadoop. This software can be basically used for 
Data mining purpose. It runs on top of Hadoop.
Sqoop
Sqoop is a tool that is used to connect Hadoop with various relational databases that are 
used to transfer data.
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