A repository to continue my education on Azure Data Services.
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Updated
Apr 7, 2023 - Python
A repository to continue my education on Azure Data Services.
Azure Logic App to Pause, Resume, Dial-Up and Dial-Down a Azure Synapse Dedicated SQL Pool
This project is a comprehensive data engineering solution that extracts HR data from a GitHub repository, performs data transformations using Azure services, and creates an interactive HR dashboard using Power BI. The goal is to enable HR professionals and decision-makers to gain insights from the HR data for better workforce management.
Building a pipeline that can handle incremental load of data from on-premises and cloud service to Azure Data Lake
Solution accompanying the article on Serverless architectures
A B2B solution and architecture. This includes code for Azure Function App, SQL Server. Integration with azure synapse and event hubs as well.
Data Engineering Project using Tokyo Olympic Data
Processed and Ingested Netflix Movies and TV Shows content in Azure Cosmos DB using AWS and Azure Cloud services. Further visualized the final data using PowerBI.
Tokyo-olympic-azure-data-engineering-end-to-end-project
Data pipeline that processes Formula1 data with Azure Databricks, DeltaLake, and Azure Data Factory
Unofficial samples that utilise Pigment's API to integrate with data movement and serverless solutions.
Azure Synapse and SAP SFLIGHT demo application integration scenario
Pipeline de dados no Azure para base de imóveis, com estrutura em três camadas (unbound, silver, gold) e trigger automática a cada hora para atualização consistente.
Data Engineering Project - Python, PySpark & SQL - Azure Data Factory (ADF), DataBricks, Synapse Analytics, Azure Data Lake Storage (ADLS) Gen2, Power BI, Tableau and Looker Studio
A simple pipeline to transform data within Azure Data Factory using Azure Databricks. Although it is written in Scala the same can be replicated in Python.
Data engineering project using Azure Data Factory and Apache Airflow
In this project we will learn how to deal with huge volumes of data using Databricks and build an ETL pipeline on it.
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