Best free data analytics tools, 2018

Data analytics is increasingly important for businesses looking to uncover insights that might be hidden in a vast sea of data. Organizations can gain a tremendously valuable perspective on their customers and business objectives using tools that are designed to organize, categorize and infer statistical conclusions from various sources of data.

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Enterprises have many considerations to weigh and choices to make when evaluating data analytics tools, but finding the right application and using its features effectively can lead to dramatic transformation.

We’ve reviewed dozens of providers to identify the best free data analytics software available today. After weighing their strengths and limitations, studying reviews by industry leaders and analyzing rankings from various research firms, we’ve selected the following seven tools (presented in alphabetical order) to help you find the solution that’s best for you.

DataMelt, also referred to as DMelt, is a computational platform for statistical analysis of large data and scientific visualization. The program is most frequently used in natural sciences, engineering, and modeling and analysis of financial markets. The platform supports many programming languages including Python, BeanShell, Groovy, Ruby, Java and others.

Organizations can access vast libraries via dynamic scripting, including more than 40,000 Java classes for computation and visualization and 500 Python modules. More advanced features require a developer or commercial license, but the free edition of DataMelt includes many of the key features required to explore, analyze and visualize data.

DataMelt runs on Windows, Linux, macOS and Android devices.

http://jwork.org/dmelt/

The KNIME Analytics Platform is designed to help organizations manipulate, analyze and model data through visual programming. The software includes more than 1,000 modules, hundreds of ready-to-run examples and a range of integrated tools to help users discover potential insights hidden in their data and predict futures with the aid of machine learning.

Instead of writing code, KNIME enables organizations to drag and drop connection points between activities. The data analysis tool also supports data blending among simple text files, databases, documents, images, networks and Hadoop-based data in a single visual workflow. KNIME Analytics Platform is open source and is updated with new releases on a bi-annual basis.

KNIME is available for Windows, macOS and Linux devices.

https://www.knime.com/knime-analytics-platform

OpenRefine, formerly Google Refine, helps organizations get a handle on messy data. Google stopped supporting the project in 2012, but the application is still available and is updated regularly by volunteers. OpenRefine can perform various tasks on data, including cleaning, transforming and formatting data to make it more suitable for data analysis and exploration. The tool also enables users to fetch data from external web services to reconcile and match data from various sources.

OpenRefine is not the best tool for vast databases, but it remains an important and well regarded option for many organizations because of the significant amount of time that analysts spend cleaning data for predictive modeling.

OpenRefine is available for download on Windows, macOS and Linux.

http://openrefine.org/

Orange is an open source data analysis and visualization tool developed at the University of Ljubljana in Slovenia. Users can mine data via visual programming or Python scripting in a terminal window; explore statistical distributions, box plots or scatter plots; and dive deeper into their data with decision trees, hierarchical clustering, heatmaps and linear projections.

Orange’s graphical user interface enables users to focus on exploratory data analysis instead of coding. The tool also has components for machine learning and add-ons that extend the functionality of data mining from external sources to perform natural language processing, text mining, bioinformatics, network analysis and association rules mining.

Orange supports Windows, macOS and Linux.

https://orange.biolab.si

The R programming language is widely used for research in statistical methodology. Organizations can also take advantage of an integrated suite of software for data manipulation, calculation and graphical display. Key statistical features include linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering.

R runs on Unix, Windows and macOS.

https://www.r-project.org/

Tableau Public is a data analysis and visualization application that enables users to publish interactive data to the web. The free version of Tableau is limited to 1 GB of data storage and 1 million rows of data. The simplicity and intuitiveness of Tableau Public has made it one of the most popular data analysis tools.

Tableau Public can mine data from Google Sheets, Microsoft Excel, CSV files, JSON files, statistical files, spatial files, web data connectors and OData. Users can generate interactive charts, graphs and maps to be shared on social media or embedded on sites for public availability. Tableau Public is available for download on Windows and macOS.

https://public.tableau.com/en-us/s/download

Trifacta Wrangler is another app designed to help data analysts clean and prepare messy data from diverse sources. Once datasets are imported to Trifacta Wrangler, the app will automatically organize and structure the data. Machine learning algorithms help prepare data for more detailed analysis by suggesting common transformations and aggregations.

Trifacta Wrangler can import data from Microsoft Excel, JSON files and raw CSV files. The tool also profiles data to indicate what percent of rows have missing, mismatching or inconsistent values, and visually categorizes data by type, such as the date or time, string or IP address associated with each data point. Trifacta Wrangler is limited to 100 MB of data and is available for download on Windows and macOS devices.

https://www.trifacta.com/products/wrangler/