There are 1 repository under adlsgen2 topic.
OctopuFS library helps managing cloud storage, ADLSgen2 specifically. It allows you to operate on files (moving, copying, setting ACLs) in very efficient manner. Designed to work on databricks, but should work on any other platform as well.
Fluentd output plugin for Azure Datalake Storage Gen2 (append support)
Procedimento para criação de um Azure Data Lake Storage usando Terraform, através de uma assinatura MS Learn Sandbox
This sample demonstrates how to create a Linux Virtual Machine in a virtual network that privately accesses a blob storage account using an Azure Private Endpoint.
Explore the Tokyo Olympics data journey! We ingested a GitHub CSV into Azure via Data Factory, stored it in Data Lake Storage Gen2, performed transformations in Databricks, conducted advanced analytics in Azure Synapse, and visualized insights in Synapse or Power BI.
Data Engineering Project on Supply Chain ETL. Creating a dynamic ADF pipeline to ingest both Full Load and Incremental Load data from SQL Server and then transform these datasets based on medallion architecture using Databricks.
Using SAS to authenticate and access to ADLS Gen 2 from Azure Databricks
COVID19-ADF is a project that leverages Azure services to collect, analyze, and visualize COVID-19 data. With seamless data integration and advanced analytics, it provides valuable insights into the pandemic's impact, enabling informed decision-making in the fight against COVID-19.
Implementation of most useful services of Azure Data Platform.
POC projects working on Cloud Platforms
Code/Utility to recursively traverse a given Azure Data Lake Gen2 account and find the size of various Containers and Folders
Creating a pipeline that will automatically create View of data in Synapse, whenever data arrives in ADLS Gen2.
This repo contains code specific to the SQL-driven spark aggregation framework to be executed in the Databricks cluster that integrates with the Azure storage account.
"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."
Deploy apache spark in client mode on Kubernetes cluster, integrate with Jupyter notebook through Jupyterhub server.
Azure Data Lake Gen2 Backup Sync
AirBnB CDC Ingestion Pipeline: Near Real-Time Change Data Capture (CDC) Pipeline on Azure for Seamless Integration of Continuous Data Streams
Azure data migration project to migrate data from on-prem SQL Server to Azure cloud using meta-data driven approach.
Data files for azure cloud data engineering project
Implemented Azure Databricks for real-time data processing and governance using Unity Catalog, Spark Structured Streaming, Delta Lake features, Medallion Architecture, and end-to-end CI/CD pipelines. Focused on incremental loading, compute cluster management, maintaining data quality, and creating workflows.