Nowadays, Companies that are not leveraging data analytic tools and techniques are falling apart. Since data analytics tools capture in products that automatically collect, clean, and analyze data, delivering information and predictions, you can improve prediction accuracy and refine the models.  If you are a Big Data professional or data scientist, you will be working with large datasets on a daily basis. Employers are willing to pay analysts with expertise in querying and programming. Languages like SQL, Java, Python, R are in high demand for working with these analytic tools.

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Nowadays, Companies that are not leveraging data analytic
tools and techniques are falling apart.
Since data analytics tools capture in products that automatically
collect, clean, and analyze data, delivering information and
predictions, you can improve prediction accuracy and refine the
models.
If you are a Big Data professional or data scientist, you will be
working with large datasets on a daily basis.
Employers are willing to pay analysts with expertise in querying
and programming. Languages like SQL, Java, Python, R are in
high demand for working with these analytic tools.

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We present 4 of the most effective data analysis tools used by
the analysts at the workplace.

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1.Rapid Miner
Rapid-miner is a popular choice among data analysts. The
platform is provided as a service, so there is no need for writing
any code. This platform is able to take any kind of data and
transform it to give customized results.
This award winning tool finds application in the following areas:
• Statistical analysis
• Predictive analytics
• Data mining
• Machine learning

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2.Google Fusion Tables
You can filter data and make changes to hundreds of data rows
as per the needs. It also allows you to merge tables with varying
content. It helps in creating high quality data visualizations.
This web service helps to visualize data with the help of select
features. Data study includes using lineplots, scatterplots, bar
charts, pie charts and geographical maps.

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3.Gephi
The tool helps you present complex graph data as a map and
create reports. The tool has a simple layout for reading and
can highlight important nodes with colors and shapes.
This is an open source software developed in France and
written in Java. It is used to explore various kinds of data and
create data visualization reports.

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4. Weka
The Weka tool provides support for essential data mining
tasks. The tool functionality is used for the following stages:
• Data pre-processing
• Clustering
• Classification
• Regression
• Visualization
• Feature selection

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