JSON-driven ETL pipeline framework prototype
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Updated
Mar 25, 2020 - Python
JSON-driven ETL pipeline framework prototype
A deployed machine learning model that has the capability to automatically classify the incoming disaster messages into related 36 categories. Project developed as a part of Udacity's Data Science Nanodegree program.
A project structure for doing and sharing data engineer work.
Build ETL piplines on AirFlow to load data from BigQuery and store it in MySQL
An extension that registers all pharmacies in Argentina.
This repo contains the DAGs that run on my local Airflow environment. I use the local environment to test my DAGs before deploying them to virtual machines via Kubernetes
Data pipelines from re-usable components
Data integration platform for LLMs. Connect to SaaS tools with turnkey auth and sync documents from N data sources with only one integration
Weaving together different threads (services like image/audio converse, ETL services, etc.) to enable the World Wide Flow
The open-source Useful SDK. One python decorator in the Useful library allows for full observability of Python functions within an ETL.
A Python and Spark based ETL framework. While it operates within speed limits that is framework and standards, but offers boundless possibilities.
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