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4 Must-Have Data Analytics Tools For Your Business
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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.
1.Rapid Miner
3.Gephi
2.Google Fusion Tables
4. Weka
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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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