dbt + Metabase integration
-
Updated
Jun 21, 2024 - Python
dbt + Metabase integration
Data pipeline performing ETL to AWS Redshift using Spark, orchestrated with Apache Airflow
Hypergol is a Data Science/Machine Learning productivity toolkit to accelerate any projects into production with autogenerated code, standardised structure for data and ML and parallel processing out-of-the-box.
📈 🐍 Multidimensional synthetic data generation with Copula and fPCA models in Python
This repository is a working ETL framework which utilizes user data from Spotify API using ➲Python for Extraction and Transformation ➲SQL for Data Loading and Staging ➲Airflow for Data Orchestration and Monitoring ➲PowerBI for Reporting
Data model for the Participatory Knowledge Practices in Analogue and Digital Image Archives (PIA) project
Formula 1 race data engineering project which utilises azure services and databricks to ingest and analyse the data.
This project carried out as the final capstone project of the Udacity Data Engineering nanodegree program. It involves Extracting, Loading, and Transforming of datasets of different file formats from the web (downloadable,), to the lake (S3), and then the warehouse (Redshift)
⚙️ ETL pipeline on AWS using S3 and Redshift
An end to end data engineering project aiming to build an ELT data pipeline that generate insights into ads campaign.
Made in collaboration with Eskil Pedersen and Mats Undseth. The project consists of 1) designing the entity relationship model , 2) creating data base that stores data about coffees and people's reviews of the different coffees and 3) writing SQL quieries and relevant Python code.
Add a description, image, and links to the data-modelling topic page so that developers can more easily learn about it.
To associate your repository with the data-modelling topic, visit your repo's landing page and select "manage topics."