kuwala-io

In this episode we discuss how to use Kuwala efficiently to perform demand forecasting similarly like Uber does. We guide you through the three biggest challenges of New Mobility that drive the ROI of the assets (e.g. scooters) and how to implement external data to identify bottlenecks in your demand, operations plan and expansion strategy. Hope you enjoy this episode!

Open Source Solutions are booming. Open Source projects are easy to clone from Github or Gitlab. The projects´ licenses mostly allow you to use the code in your own product with a kind of contribution. Especially the data engineering space is exploding within the Open Source Landscape since Open Source software is reliable and many contributors extend the solutions. In this episode, we give a brief overview of the data science workflow. The projects we are talking about are available on the following Links: 

• Airbyte | Python (Data Integration): https://github.com/airbytehq/airbyte
• Great Expectations | Python (Data Governance): https://github.com/great-expectations/great_expectations
• Marquez | Java (Data Lineage): https://github.com/MarquezProject/marquez
• Data Explorer | R ( Data Exploration): https://github.com/boxuancui/DataExplorer
• DBT | SQL (Data Analytics): https://github.com/dbt-labs/dbt

This is our very first episode. Who are we? We are Matti and Florian. We both started working on Kuwala, which is an open source data framework for Data Scientists and Data Engineers. In this episode we explain ourselves: Where are we right now with Kuwala and what's coming soon....