Practice with Azure Synapse Analytics/Databricks Pipeline
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Updated
Nov 25, 2022
Practice with Azure Synapse Analytics/Databricks Pipeline
Scala code to convert CSV files stored in Azure Blob Storage to Parquet and store into Azure Storage, using Data bricks notebook and ARM template to run the notebook as a Azure Data Factory Job
The future of sustainability and training: involvement and performance of companies and strategic suppliers
A Re-do of Perth City Properties project using Azure Data Engineering technologies such as Azure Data Factory (ADF), Azure Data Lake Storage Gen2, Azure Blob Storage, Azure Databricks.
Data pipeline project (ELT using Microsoft Azure)
This is a project where data ingestion, data transformation, data preparation and other data activities including Azure SQL. Making pipelines production ready, monitoring and CI/CD implementation.
Bugs In Cloud - Elenco dei Video
Contains solutions/versions of Batch Data Pipelines created on Azure Data Factory
Tokyo Olympics Data Analysis: Creating a ETL pipeline using Azure Data Factory to ingest data, transform it using Azure Databricks and querying and building reports using tools like Synapse Analytics and PowerBI
Covid ETL Project using Azure Data Engineering Stack
A Covid-19 Project on Azure Cloud
The aim of this project is to build a cost efficient Data Warehouse on Amazon's Retail sales data and perform Customer lifetime value analyses.
This project presents a sophisticated data-driven web application that integrates React for frontend visualization, NodeJS for backend data retrieval, and Microsoft's Cosmos DB for data storage. Leveraging the fault tolerance, partitioning, replication, and global distribution advantages of Cosmos DB.
This Azure Data Factory (ADF) pipeline will be automatically triggered whenever a CSV file is dropped in a specific location within the Storage Account Container. The pipeline reads the contents of the CSV file, converts it into an HTML table, and then sends a notification containing the newly created table to the designated Microsoft Teams channel
Repository created for programming and development in the Azure Data Enginner.
Copying data from Amazon S3 bucket to Azure Blob container by using Azure Data Factory pipeline. This Data is mounted to Databricks and further analysis is done using Spark SQL.
Ingested Tokyo Olympic data into Azure Data Lake using Azure Data Factory. Enhanced data quality with Apache Spark on Azure Databricks. Optimized SQL queries on Synapse Analytics, reducing execution time. Developed engaging Power BI dashboards, boosting user engagement creating KPI's with DAX.
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