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Mastering Azure Data Engineering: Part 4 - Hands-On
1,351 students
Mastering Azure Data Engineering: Part 4 - Hands-On
Azure Data Mastery: Techniques & Best Practices for Data Factory, Synapse Analytics, DP-900, and DP-203
Created byLakshmi Narayana Singilidevi
Last updated 6/2024
English
What you'll learn
- Integrate Azure Blob Storage with SQL databases using Azure Data Factory, enabling seamless data transfer and synchronization.
- Automate the creation of tables within Azure Data Factory pipelines, streamlining data ingestion and processing workflows.
- Implement parameterization techniques in Azure Data Factory to enhance pipeline flexibility and reusability.
- Utilize stored procedure activities within Azure Data Factory to execute complex data processing logic and manage database operations efficiently.
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Course content
1 section • 7 lectures • 1h 50m total length
Requirements
- Yes, learners will need access to an Azure subscription or Azure Free Trial to complete the hands-on labs and exercises in this course. A subscription allows students to interact with Azure services directly, gaining practical experience in deploying, managing, and optimizing Azure Data Services. The Azure Free Trial provides a limited-time opportunity to explore Azure services with a credit balance, making it an ideal option for learners who do not have an existing subscription.
Description
Mastering Azure Data Engineering continues with Part 4, focusing on advanced Azure skills crucial for proficient data engineering. This module delves into integrating Azure Blob storage with SQL databases, automating table creation, parameterization techniques, stored procedure activities, and data transformation using derived columns. Participants will engage in step-by-step tutorials, hands-on labs, and practical exercises to solidify their understanding and expertise in these essential Azure Data Factory functionalities. By the end of the course, learners will possess the skills necessary to streamline data integration, automation, and transformation processes within Azure Data Factory, empowering them to tackle complex data engineering challenges with confidence.
Course Objectives:
Master the process of integrating Blob storage with SQL databases in Azure Data Factory.
Automate table creation tasks within Azure Data Factory pipelines for enhanced efficiency.
Implement parameterization techniques to enhance flexibility and reusability in data workflows.
Utilize stored procedure activities effectively for executing database operations within Azure Data Factory.
Learn how to transform data using derived columns, enabling advanced data manipulation capabilities.
Efficiently filter data using the Select All activity in Azure Data Factory to optimize data processing workflows.
Target Audience:
Experienced Data Engineers
Data Architects
Azure Developers
IT Professionals seeking advanced Azure data engineering skills
Prerequisites:
Proficiency in Azure Data Factory fundamentals.
Familiarity with SQL databases and data transformation concepts.
Basic understanding of Azure services and cloud computing principles.
Delivery Format:
Instructor-led training sessions
Hands-on labs and tutorials
Who this course is for:
- This course is ideal for: 1. Aspiring data professionals seeking to enhance their knowledge and skills in Azure Data Services. 2. IT professionals aiming to validate their expertise with the DP-900 certification. 3. Developers interested in leveraging Azure for data storage, analytics, and visualization. 4. Anyone looking to transition into a career involving cloud-based data management and analytics. 5. Students and learners eager to explore the fundamentals of Azure Data Services in a practical, hands-on manner.