Essential SQL: Azure Data Factory and Data Engineering

Data Engineering using ADF | Azure Data Factory | Data Mapping Flows | SQL Stored Procedure | Data Engineering

Preview this Course

  GET COUPON CODE

Use Azure data factory to automate data engineering tasks. This is a great course to introduce yourself to Azure Data Factory’s capabilities. We’ll look at the data factory from a data engineer perspective.

Through examples we’ll work side by side to create an Extract Transform and Load process to ingest movie rating data.

We are going to explore three different ways to transform your data.

The first is by using Azure Data Mapping flows. These are great no-code ways to do ETL.

We’ll then look at how you can do the same transformations using Python. This way, if you love Python, you know a solid way to use Azure data factory to work with your data.

Lastly, we’ll look at how you can create pipelines to use your knowledge of SQL and stored procedures.

What you’ll like about this course is that once you learn one way to transform the data, you can use that knowledge to learn about the other methods. So, if you’re a SQL expert but soft on python, you can learn the SQL way before trying another mapping method.  In the end you come out learning and appreciating alternative methods to ingesting, transforming, and storing data.

Who this course is for:

• Aspiring Data Engineers: Individuals who are new to data engineering and want to learn how to use Azure Data Factory to build data solutions.
• Business Analysts: Analysts who work with data to make business decisions. Understanding data engineering can help them better utilize and secure data for decision-making.
• Business Intelligence Developers: BI developers seeking to automate data pipelines for their reporting and analytics needs using Azure Data Factory.
• Cloud Architects: Professionals responsible for designing and implementing cloud solutions. They may want to understand how Azure Data Factory fits into their architecture.
• Data Analysts: Analysts who want to expand their skills by learning how to move and transform data using Azure Data Factory for better analysis.
• Data Architects: Professionals responsible for designing data architectures and systems. They need to ensure that the data solutions they design are secure, scalable, and well-managed.
• Data Scientists: Data scientists who want to work with clean and well-organized data, making Azure Data Factory knowledge beneficial for data preparation.
• Database Administrators: DBAs looking to integrate Azure Data Factory into their data management processes, especially for data movement and ETL (Extract, Transform, Load) tasks.
• Software Developers: Developers who want to gain expertise in building data solutions and working with databases. They might be interested in integrating data management and security practices into their software development workflows.
• System Administrators: IT administrators responsible for managing Azure accounts and resources may need to understand Azure Data Factory for resource allocation and monitoring.