amanjot-git / azuresql

Learning Azure Data Fundamentals of Relational and Non Relational Data with Microsoft Learn Platform

📄 About

This repository offers an engaging hands-on adventure, guiding you through practical labs and projects designed to excel in data fundamentals and Azure SQL. It covers the utilization of Azure SQL, Azure Blob Storage, Azure Cosmos DB, and real-time analytics, sourced from Microsoft's Learning platform.

📑 Courses and Links

✅ 01. Microsoft Azure Data Fundamentals: Explore core data concepts

✅ 02. Microsoft Azure Data Fundamentals: Explore relational data in Azure

✅ 03. Azure SQL fundamentals

✅ 04. Microsoft Azure Data Fundamentals: Explore non-relational data in Azure (Azure blob storage, Azure DataLake Storage Gen2, Azure Files, Azure Tables, Azure storage, Azure Cosmos DB)

✅ 05. Microsoft Azure Data Fundamentals: Explore data analytics in Azure (Azure Synapse Analytics, Azure Stream Analytics, Microsoft Fabric, Power BI)

🛠️ Tools

The following tools can be used to complete this learning path:

(Azure portal, SSMS, Azure Data Studio, Azure SQL , Azure storage, Azure Synapse Analytics, Azure Stream Analytics, Microsoft Fabric, Power BI)

📂 Projects

✅ Exploring AdventureWorks database on Azure SQL [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-01-sql-lab.html)]

✅ Deploy SQL Database [(https://learn.microsoft.com/en-gb/training/modules/azure-sql-deploy-configure/3-exercise-deploy-database)]

✅ Configure Azure SQL Database and Azure SQL Managed Instance [(https://learn.microsoft.com/en-gb/training/modules/azure-sql-deploy-configure/5-configure-database)]

✅ Verify SQL Database using Azure Data Studio or SSMS [(https://learn.microsoft.com/en-gb/training/modules/azure-sql-deploy-configure/4-exercise-verify-database)]

✅ Load Data into Azure SQL [(https://learn.microsoft.com/en-gb/training/modules/azure-sql-deploy-configure/8-exercise-load-data)]

✅ Data classification, dynamic data masking, and SQL audit [(https://learn.microsoft.com/en-gb/training/modules/azure-sql-secure-data/9-exercise-data-classification-masking-audit]

✅ Azure storage account [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-02-storage-lab.html)]

✅ Azure Cosmos DB [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-03-cosmos-lab.html)]

✅ Data Analytics in Azure with Azure Synapse Analytics [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-04-synapse-lab.html)]

✅ Data Analytics in Microsoft Fabric [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-04b-fabric-lake-lab.html)]

✅ Azure Stream Analytics [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-05-stream-lab.html)]

✅ Spark Streaming in Azure Synapse Analytics [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-05a-stream-with-spark.html)]

✅ Real-time analytics in Microsoft Fabric [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-05c-fabric-realtime-lab.html)]

✅ Data visualization with Power BI [(https://microsoftlearning.github.io/DP-900T00A-Azure-Data-Fundamentals/Instructions/Labs/dp900-pbi-06-lab.html)]

Disclaimer: This repository contains links and references directing users to content on the Microsoft Learn platform. The provided links are intended solely for educational purposes and to facilitate access to official Microsoft learning resources. The repository owner is not responsible for the content on external platforms and does not endorse or guarantee the accuracy, completeness, or suitability of the information provided on the Microsoft Learn platform. Users are encouraged to review and comply with the terms of use, privacy policies, and any applicable guidelines provided by Microsoft Learn. The repository owner shall not be held liable for any consequences or issues arising from the use of external links and resources.