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Azure Data Engineering Labs - DP-203

This repository contains the hands-on labs I completed as part of my learning journey in Azure Data Engineering, specifically for the DP-203 exam. These labs have helped me gain practical experience working with Azure Synapse Analytics, SQL, and Data Lake, and they cover the following areas:

Labs Overview

1. Explore Azure Synapse

  • Description: This lab introduces the Azure Synapse platform, helping me understand its capabilities for data processing, analytics, and integration.
  • Key Learnings:
    • Navigating and exploring the Azure Synapse Analytics environment.
    • Understanding the integration between Azure Synapse and other Azure services.

2. Analyze Data with SQL

  • Description: In this lab, I practiced querying data using SQL within Azure Synapse Analytics. I learned to retrieve valuable insights from large datasets.
  • Key Learnings:
    • Writing SQL queries for data analysis.
    • Filtering, grouping, and aggregating data to derive insights.
    • Using advanced SQL functions in Azure Synapse.

3. Transform Data with SQL

  • Description: This lab focused on transforming data using SQL. I learned various techniques to clean, manipulate, and reshape data within Azure Synapse.
  • Key Learnings:
    • Performing data transformations with SQL.
    • Applying functions to clean, aggregate, and manipulate datasets.

4. Create a Lake Database

  • Description: In this lab, I created a lake database within Azure Data Lake, organizing data for further analysis and processing.
  • Key Learnings:
    • Setting up a lake database in Azure Data Lake.
    • Managing and organizing data for efficient analysis.

What I Learned

These labs have provided me with hands-on experience in key areas of Azure Data Engineering:

  • Navigating Azure Synapse Analytics.
  • Using SQL for data analysis and transformation.
  • Working with Azure Data Lake for organizing and storing data.

I'm excited to continue expanding my knowledge and apply these skills to real-world projects!

Technologies Used

  • Azure Synapse Analytics
  • SQL
  • Azure Data Lake

Conclusion

These labs have been an excellent resource in mastering the practical skills required for Azure Data Engineering. Looking forward to applying these learnings in more complex projects!

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