RATH is beyond an open-source alternative to Data Analysis and Visualization tools such as Tableau. It automates your Exploratory Data Analysis workflow with an Augmented Analytic engine by discovering patterns, insights, causals and presents those insights with powerful auto-generated multi-dimensional data visualization.
Get started with RATH now!
Feature highlights | Walkthroughs | Developer Documentation | Project Status | Community | Contributions
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🤖 Mega-auto exploration: Augmented analytic engine for discovering patterns, insights, and causals. A fully-automated way to explore your data set and visualize your data with one click.
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AutoVis: Auto-generated multi-dimensional data visualization based on the effectiveness score.
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👓 Data Wrangler: Automated data wrangler for generating summary of the data and data transformation.
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🛠 Semi-auto exploration: Combines automated data exploration and manual exploration. RATH will work as your copilot in data science, learn your interests and uses augmented analytics engine to generate relevant recommendations for you.
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🎨 Data painter: An interactive, instinctive yet powerful tool for exploratory data analysis by directly coloring your data, with further analytical features. A video about data painter here
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📊 Dashboard: build a beautiful interactive data dashboard (including a automated dashboard designer which can provide suggestions to your dashboard).
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🚧 Causal Analysis: Provide causal discovery and explanations for complex relation analysis.
RATH support data preparation with black magic like predictive transformation operations. It will automatically generate suggestions of transformations and cleaning, etc.
Assisted with AI, RATH can help you with your data analysis. Just provide RATH with some input and it will learn about your interests and suggest analysis directions to take.
Manual Exploration is an independent embedding module. You can use it independently in your apps. For more details, refer to the README.md in in
packages/graphic-walker/README.md.Install Graphic Walker
yarn add @kanaries/graphic-walker # or npm i --save @kanaries/graphic-walker
Data Painter Video 🔥 on Youtube
Causal analysis could be defined as the way to identify and examine the causal relationship between variables, which can help explore the data, create better prediction models and make business decission.
RATH's causal analysis feature include:
- Causal Discovery
- Editable graphical causal models
- Causal interpretability
- Interactive tools for deeper exploration
- What-if analysis
For more about Causal Analysis features, refer to RATH Docs.
RATH supports a wide range of data sources. Here are some of the major database solutions that you can connect to RATH:
If you want to add support for more database types or data engines, feel free to Contact us
We encourage you to check out our RATH Docs for references and guidance. RATH Docs are scripted and maintained by technical writers and editors who collectively follow a standardized style guide to produce clear and consistent documentation.
Kanaries community is a place to have open discussions on features, voice your ideas, or get help with general questions. Get onboard with us through the following channels:
Our developer community is the backbone of the ongoing RATH project. We sincerely welcome you to join our community, participate in the conversation and stay connected with us for the latest updates.
Feel free to contribute to the RATH project, submit any issues on our GitHub page, or split your grand new ideas in our chats.
Please consider sharing your experience or thoughts about Kanaries RATH with the border Open Source community. It really does help!
Please check out the Contributing to RATH guide for guidelines about how to proceed.
Thanks to all contributors ❤️
Rath is an automated data analysis and visualization tool (auto-EDA).
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/.
Branded icons are licensed under their copyright license.
Have fun with data! ❤️