Master Data Engineering using Azure Data Analytics
Why take this course?
🌟 Master Data Engineering using Azure Data Analytics 🌟
Welcome to the comprehensive course designed to empower you with the skills to master data engineering using the robust suite of services provided by Microsoft Azure. This course is crafted for professionals who aspire to build scalable and efficient Data Pipelines, harnessing the full power of Azure's Data Analytics Stack. 🛠️💧
Course Instructor: Durga Viswanatha Raju Gadiraju
Course Description:
Data Engineering is not just about moving data from point A to B. It's an art and a science, requiring a deep understanding of data sources, processing capabilities, and downstream systems. In this course, Durga Viswanatha Raju Gadiraju will guide you through the process of constructing resilient Data Engineering Pipelines using the Azure Data Analytics Stack. This includes leveraging services such as:
- Azure Storage (Blob and ADLS) for secure and scalable data storage.
- ADF (Azure Data Factory) for both ETL (Extract, Transform, Load) processes and orchestration tasks.
- Azure Synapse for powerful Data Warehouse solutions.
- Azure Databricks for advanced analytics on Big Data pipelines.
Course Outline:
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Setting Up Your Environment:
- Get comfortable with the development environment using VS Code on both Windows and Mac systems.
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Getting Started with Azure Portal:
- Sign up for an Azure Portal account with ease.
- Explore billing details and secure your USD 200 credit, available for up to a month.
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Leveraging Azure Storage as a Data Lake:
- Dive into using Azure Storage as your central repository for large-scale data.
- Master managing files within Azure Storage using tools like Azure Storage Explorer.
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Data Engineering with ADF Data Flow:
- Understand and apply ETL processes using ADF Data Flow.
- Learn to set up Linked Services, Data Sets, and ensure baseline load handling.
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Building Robust Pipelines with ADF Pipeline:
- Develop comprehensive pipelines for orchestrating various data tasks.
- Parameterize your pipelines for maximum flexibility and efficiency.
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Performance Tuning Techniques in ADF:
- Discover how to optimize your ADF Pipelines with techniques like controlling partitions and leveraging custom Integration Runtimes (IR).
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Working with Azure SQL:
- Set up and configure Azure SQL for your data needs.
- Create tables, run queries, and manage database operations.
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Data Transfer with ADF Data Copy:
- Utilize ADF Data Copy to transfer data between different sources and targets, including databases.
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Exploring Synapse Analytics for Data Warehousing:
- Get familiar with both serverless and dedicated pools in Synapse Analytics.
- Set up a dedicate pool for ETL processes using ADF.
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Building ETL and Orchestration Pipelines:
- Construct ETL pipelines using ADF Data Flow and orchestrate them with ADF Pipeline.
- Integrate Azure SQL and Azure Synapse within your data workflows.
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Big Data Processing with Azure Databricks:
- Set up Azure Databricks for Spark-based Big Data processing.
- Manage secrets and integrate with ADLS for seamless operations.
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Understanding Apache Spark with Azure Databricks:
- Gain insights into Spark SQL and PySpark DataFrame APIs using Azure Databricks.
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ELT Pipeline Development in Databricks:
- Build ELT pipelines using Databricks Jobs and Workflows, defining tasks with Pyspark and Spark SQL.
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Orchestrating Databricks Notebooks with ADF Pipelines:
- Learn how to use ADF Pipelines to manage and execute Databricks Notebooks as part of your data engineering process.
By the end of this course, you will have a solid understanding of building scalable and efficient Data Engineering solutions using Azure's Data Analytics services. You will be equipped with the practical skills needed to implement real-world data pipelines that are both robust and cost-effective. 🚀📊
Join us on this journey to become a master in Data Engineering with Azure! Enroll now and transform your career. Let's embark on this learning path together! 🎓✨
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