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https://github.com/kuwala-io/kuwala

Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such as Airbyte, dbt, or Great Expectations together in one intuitive interface built with React Flow. In addition we provide third-party data into data science models and products with a focus on geospatial data. Currently, the following data connectors are available worldwide: a) High-resolution demographics data b) Point of Interests from Open Street Map c) Google Popular Times
https://github.com/kuwala-io/kuwala

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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Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such as Airbyte, dbt, or Great Expectations together in one intuitive interface built with React Flow. In addition we provide third-party data into data science models and products with a focus on geospatial data. Currently, the following data connectors are available worldwide: a) High-resolution demographics data b) Point of Interests from Open Street Map c) Google Popular Times

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README 

        
[![Slack](https://img.shields.io/badge/slack-chat-orange.svg)](https://join.slack.com/t/kuwala-community/shared_invite/zt-l5b2yjfp-2cdhReNACXDkLhuh0jFzZw)

![License](https://img.shields.io/github/license/kuwala-io/kuwala)








  

  




Kuwala is **the data workspace for BI analysts and engineers enabling you to build powerful analytics workflows together.** 

We are set out to bring **state-of-the-art data engineering tools** you love, such as 

[Airbyte](https://github.com/airbytehq/airbyte), [dbt](https://github.com/dbt-labs/dbt-core) and 

[Prefect](https://github.com/prefecthq/prefect) together in one intuitive interface built with 

[React Flow](https://github.com/wbkd/react-flow).



Do you want to **discuss your first contribution**, want to **learn more in general**, or 

**discuss your specific use-case** for Kuwala? Just **book a digital coffee session** with the core team 

[here](https://calendly.com/kuwala_io/kuwala-community-chat).



![Collaboration between BI analysts and engineers](./docs/images/kuwala_collaborative_cycle.png)



Kuwala stands for **extendability, reproducibility, and enablement**. Small data teams build data products fastly and 

collaboratively. Analysts and engineers stay with their strengths. Kuwala  is the tool that makes it possible to keep a 

data project within scope while having fun again.



- **Kuwala Canvas runs directly on a data warehouse** = Maximum flexibility and no lock-in effect

- **Engineers enable their analysts** by adding transformations and models via dbt or new data sources through Airbyte

- **The node-based editor enables analyst** to build advanced data workflows with many data sources and transformations through simple drag-and-drop

- **With models-as-a-block** the BI analyst can launch advanced Marketing Mix Models and attributions without knowing R or Python






### Extract and Load with Airbyte



Currently we support the following databases and data warehouses



- [x] Postgres

- [x] BigQuery

- [x] Snowflake



 For connecting and loading all your tooling data into a data warehouse, we are integrating with Airbyte connectors. 

 For everything related to third-party data, such as POI and demographics data, we are building separate data pipelines.



### Transform with dbt



To apply transformations on your data, we are integrating dbt which is running on top of your data warehouses. 

Engineers can easily create dbt models and make them reusable for the frontend. We have already a catalog of several 

transformations that you can use on the canvas. The complete documentation can be found here: 

[https://docs.kuwala.io/](https://docs.kuwala.io/transformation-catalog)



### Run a Data Science Model



We are going to include open-source data science and AI models as blocks (e.g., 

[Meta's Robyn Marketing Mix Modeling](https://github.com/facebookexperimental/Robyn)).



### Report



You can easily connect your preferred visualization tool and connect it to a saved table on the canvas in the future. 

We will make the results exportable to Google Sheets and also available in a Medium-style markdown editor.



---



# How can I use Kuwala?



### Canvas



With the canvas you can connect to your data warehouse and start building data pipelines. To start the canvas, simply

run the following command from inside the root directory:



```zsh

docker-compose --profile kuwala up

```



Now open http://localhost:3000 in your browser, and you are good to go. 🚀



### Third-party data connectors



We currently have five pipelines for different third-party data sources which can easily be imported into a Postgres 

database. The following pipelines are integrated:



 - [Admin Boundaries](https://github.com/kuwala-io/kuwala/tree/master/kuwala/pipelines/admin-boundaries/README.md)

 - [Google POIs](https://github.com/kuwala-io/kuwala/tree/master/kuwala/pipelines/google-poi/README.md)

 - [Google Trends](https://github.com/kuwala-io/kuwala/tree/master/kuwala/pipelines/google-trends/README.md)

 - [OSM POIs](https://github.com/kuwala-io/kuwala/tree/master/kuwala/pipelines/osm-poi/README.md)

 - [Population Density](https://github.com/kuwala-io/kuwala/tree/master/kuwala/pipelines/population-density/README.md)



### Using Kuwala components individually



To use Kuwala's components, such as the data pipelines or the Jupyter environment, individually, please refer to the

[instructions under `/kuwala`](https://github.com/kuwala-io/kuwala/blob/master/kuwala/README.md).



---



# Use cases



- [How to build an Uber-like analytics system with Kuwala](https://kuwala.io/data-pipelines/how-to-build-an-uber-like-intelligence-system-for-your-new-mobility-startup-without-a-big-data-team/)

- [Perform location analytics for a grocery store with Kuwala](https://kuwala.io/case-studies/why-instant-grocery-delivery-should-follow-a-data-driven-path-like-uber-to-survive-part-1/)

- [Querying the most granular demographics data set with Kuwala](https://kuwala.io/data-pipelines/querying-the-most-granular-demographics-dataset/)



---



# How can I contribute?



Every new issue, question, or comment is a contribution and very welcome! This project lives from your feedback and

involvement!



## Be part of our community



The best first step to get involved is to join the 

[Kuwala Community on Slack](https://join.slack.com/t/kuwala-community/shared_invite/zt-l5b2yjfp-2cdhReNACXDkLhuh0jFzZw). 

There we discuss everything related to our roadmap, development, and support. 



## Contribute to the project



Please refer to our [contribution guidelines](https://github.com/kuwala-io/kuwala/tree/master/CONTRIBUTING.md) for further information on how to get involved.



---



# Get more content about Kuwala

  Link  | Description    

-------------|-------------

[Blog](https://kuwala.io/blog/) | Read all our blog articles related to the stuff we are doing here. 

[Join Slack](https://join.slack.com/t/kuwala-community/shared_invite/zt-l5b2yjfp-2cdhReNACXDkLhuh0jFzZw) | Our Slack channel with over 250 data engineers and many discussions.

[Jupyter notebook - Popularity correlation](https://mybinder.org/v2/gh/kuwala-io/kuwala_examples/1def41ded01dbb67ecada9dc227c834cd93d0721?urlpath=lab%2Ftree%2Fnotebooks%2F1.%20Popularity%20Correlation.ipynb) | Open a Jupyter notebook on Binder and merge external popularity data with Uber traversals by making use of convenient dbt functions. 

[Podcast](https://anchor.fm/kuwala-io) | Listen to our community podcast and maybe join us on the next show.

[Digital coffee break](https://calendly.com/kuwala_io/kuwala-community-chat?month=2022-02) | Are you looking for new inspiring tech talks? Book a digital coffee chit-chat with one member of the core team.

[Our roadmap](https://github.com/orgs/kuwala-io/projects/3/views/6) | See our upcoming milestones and sprint planing.

[Contribution guidelines](https://github.com/kuwala-io/kuwala/tree/master/CONTRIBUTING.md) | Further information on how to get involved.