RATH: Your Open-Source Ally in Data Analysis and Visualization

Introduction

In the age of data-driven decisions, RATH is here to revolutionize how you approach data analysis and visualization. Not just another open-source alternative to prominent tools like Tableau, RATH brings to the table an unprecedented automation in your Exploratory Data Analysis (EDA) workflow. Its sophisticated Augmented Analytic engine is designed to delve deep into patterns, insights, and causals, transforming them into insightful and multi-dimensional auto-generated visualizations.

Getting Started

Starting with RATH is a breeze! Test the waters with our sandbox demo of selected features, or delve deeper into our comprehensive RATH documentation. Take a few moments to watch our video introducing RATH's data painter feature, which offers a powerful, instinctive tool for EDA.

Key Features

RATH is engineered to deliver a full suite of advanced data analysis capabilities:

• AutoPilot for Data Exploration: This feature equips RATH to perform a fully automated exploration and visualization of your dataset with a single click, unveiling patterns, insights, and causals.
• Copilot for Data Exploration: As your personal data science copilot, RATH learns your intentions and provides relevant recommendations.
• Natural Language Interface: Ask your data questions in natural language and let RATH find the answers, complete with data visualizations.
• AutoVis: RATH selects and generates the most suitable visualization for your selected data, allowing you to focus on the data itself.
• Data Wrangler: This automated feature summarizes your data and handles data transformations.
• Data Painter: An interactive, analytical tool for exploratory data analysis, the Data Painter allows you to color your data directly. For a deeper understanding, watch this video on how Data Painter helps discover data insights.
• Dashboard: RATH allows you to build beautiful, interactive data dashboards, with an automated dashboard designer providing design suggestions.
• Causal Analysis: Identify and investigate causal relationships between variables to better explore your data, create predictive models, and make informed business decisions.

For more about our Causal Analysis features, check out the RATH documentation.

Supported Databases

RATH supports an extensive list of data sources, including Amazon Athena, Amazon Redshift, Apache Spark SQL, Apache Doris, Clickhouse, Apache Hive, MySQL, Postgre SQL, Apache Impala, Apache Kylin, Oracle, and AirTable. If you're interested in adding support for more database types or data engines, we welcome your input—feel free to contact us at RATH website.

Developer Documentation

As an open-source software in its alpha stage, we are working tirelessly to improve RATH's code and documentation. We appreciate any feedback or reports of bugs, as well as any feature requests. Check out the RATH documentation for references and guidance, or email us your experiences with RATH at support [at] kanaries.org.

Don’t forget to try out RATH products now!