Collection Of 10 Big Data Tools Used For Data Analysis, Part-1

By Jyoti Nigania |Email | Oct 2, 2018 | 16065 Views

There are numerous of Big Data tools for data analysis today. Data analysis is the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making. Here is the collection of top 30 Big Data Tools for Analysis in the areas of open source data tools, data visualization tools, sentiment tools, data extraction tools and databases.
Big Data Tools for analyses is divided into five parts:
  • Open Source Data Tools
  • Data Visualization Tools
  • Sentiment Analysis Tools
  • Data Extraction Tools
  • Databases
Following are 10 Open Source Data Tools:
  • Knime: KNIME Analytics Platform is the leading open solution for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist.
  • Open Refine: Open Refine (formerly Google Refine) is a powerful tool for working with messy data: cleaning it, transforming it from one format into another, and extending it with web services and external data. Open Refine can help you explore large data sets with ease.
  • R-Programming: What if I tell you that Project R, a GNU project, is written in R itself? It's primarily written in C and FORTRAN and a lot of its modules are written in R itself. It's a free software programming language and software environment for statistical computing and graphics. The R language is widely used among data miners for developing statistical software and data analysis. Ease of use and extensibility has raised R's popularity substantially in recent years. Besides data mining it provides statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and others.
  • Orange: Orange is open source data visualization and data analysis for novice and expert, and provides interactive workflows with a large toolbox to create interactive workflows to analyze and visualize data. Orange is packed with different visualizations, from scatter plots, bar charts, trees, to dendrograms, networks and heat maps.
  • Rapid Miner: Much like KNIME, Rapid Miner operates through visual programming and is capable of manipulating, analyzing and modeling data. Rapid Miner makes data science teams more productive through an open source platform for data prep, machine learning, and model deployment. Its unified data science platform accelerates the building of complete analytical workflows  from data prep to machine learning to model validation to deployment in a single environment, dramatically improving efficiency and shortening the time to value for data science projects.
  • Pentaho: Pentaho addresses the barriers that block your organization's ability to get value from all your data. The platform simplifies preparing and blending any data and includes a spectrum of tools to easily analyze, visualize, explore, report and predict. Open, embeddable and extensible, Pentaho is architected to ensure that each member of your team from developers to business users can easily translate data into value.
  • Talend: Talend is the leading open source integration software provider to data-driven enterprises. Our customers connect anywhere, at any speed. From ground to cloud and batch to streaming, data or application integration, Talend connects at big data scale, 5x faster and at 1/5th the cost.
  • Weka: Weka, open source software, is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data set or called from your own JAVA code. It is also well suited for developing new machine learning schemes, since it was fully implemented in the JAVA programming language, plus supporting several standard data mining tasks. For someone who hasn't coded for a while, weka with its GUI provides easiest transition into the world of Data Science. Being written in Java, those with Java experience can call the library into their code as well.
  • NodeXL: NodeXL is a data visualization and analysis software of relationships and networks. NodeXL provides exact calculations. It is a free (not the pro one) and open-source network analysis and visualization software. It is one of the best statistical tools for data analysis which includes advanced network metrics, access to social media network data importers, and automation.
  • Gephi: Gephi is also an open-source network analysis and visualization software package written in Java on the Net Beans platform. Think of the giant friendship maps you see that represent LinkedIn or Facebook connections. Gelphi takes that a step further by providing exact calculations.
For more insights stay tuned with us, In Part-2 will share Data Visualization Tools and Sentiment Analysis Tools.

Source: HOB