PyJaws: A Pythonic Way to Define Databricks Jobs and Workflows
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Updated
Jul 10, 2024 - Python
PyJaws: A Pythonic Way to Define Databricks Jobs and Workflows
An end-to-end data engineering pipeline that fetches data from Wikipedia, cleans and transforms it with Apache Airflow and saves it on Azure Data Lake. Other processing takes place on Azure Data Factory, Azure Synapse and Tableau.
Repository for Microsoft Databricks Training Events - Hosted by BlueGranite
[archived] A Python SDK for the Azure Databricks REST API 2.0
Free High-Quality Financial Data in Azure
Reusable Python classes that extend open source PySpark capabilities. Examples of implementation is available under notebooks of repo https://github.com/bennyaustin/synapse-dataplatform
A wrapper for the Azure Databricks REST API
Automated pipeline for energy consumption forecasting across Europe using Azure cloud and Databricks.
A demand forecasting pipeline deployed on Azure and AWS
Applying data engineering techniques to create data pipeline with Azure Cloud Computing
A data pipeline project build on databricks and azure to demostrate lifecycle of a cloud data project.
F1 Data Engineering Project on Azure Databricks!
Article Repository for: Ensemble Machine Learning Modeling for the Prediction of Artemisinin Resistance in Malaria
ETL motor racing data project using Azure Databricks, Pyspark and Azure Date Lakes
End-to-end ETL pipeline in the Microsoft Azure cloud - (Jun '24 - Jul '24)
A repository to continue my education on Azure Data Services.
This repository contains code for an end-to-end IoT data pipeline using Azure services. It ingests, processes, and stores IoT device data from AWS S3 to Azure Data Lake Storage and Azure SQL Database, leveraging Azure Data Factory and Azure Functions for seamless integration and automation.
"Explore Formula 1 data analytics with this project. Leveraging the Ergast API, it utilizes Databricks Spark for ingestion, transformation, and analysis. ADLS acts as the storage layer, while Power BI visualizes the ADLS presentation layer. Uncover insights in the world of Formula 1 through powerful data analytics."
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