Build powerful analytics workflows with Kuwala, a no-code data platform for BI analysts and engineers, with 805 GitHub stars.
805 stars54 forksJavaScriptQuality 8/10Updated 8/10/2022100% free ยท open source
What it does
Kuwala allows you to build powerful analytics workflows with a no-code data platform, integrating tools like Airbyte, dbt, and Great Expectations, and providing access to third-party geospatial data.
Install / run
Clone the Kuwala repository from GitHub using `git clone https://github.com/kuwala-io/kuwala.git`
When to use it
โขYou need to integrate multiple data sources and tools into a single analytics workflow
โขYou want to leverage geospatial data, such as demographics or point of interest data, in your analytics
โขYou prefer a visual, no-code interface for building and managing your data pipelines
Quick start
1Install the required dependencies by running `npm install` or `yarn install` in the cloned repository
2Start the Kuwala platform using `npm run start` or `yarn start`
3Access the Kuwala interface at `http://localhost:3000` and create a new workflow using the React Flow interface
4Connect to a data source, such as High-resolution demographics data or Point of Interests from Open Street Map, using the available data connectors
5Configure your workflow to transform and analyze the data using tools like Airbyte, dbt, or Great Expectations
Ready-to-paste prompt
Create a new workflow that integrates High-resolution demographics data with Google Popular Times data to analyze foot traffic patterns using `.dbt` to transform the data and `Great Expectations` to validate the results
Heads up: Kuwala requires a compatible version of Node.js (at least 14.17.0) and npm (at least 6.14.13) to run, so ensure your development environment meets these prerequisites before installing and running Kuwala
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Topics
admin-boundaries
data
data-integration
data-science
dbt
elt
google-trends
jupyter
kuwala
no-code
open-data
open-source
population
postgres
pyspark
python
react
react-flow
scraping
spatial-analysis
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