Essential SQL: Azure Data Factory and Data Engineering
Azure Data Factory | Data Engineering using ADF | Data Mapping Flows | SQL Stored Procedure | Data Engineering
Ratings 4.55 / 5.00
What You Will Learn!
- Learn how to construct ELT solutions using Azure Data Factory and SQL Server.
- Implement various ELT solutions using Mapping Data Flows, Copy Activities, and Stored Procedures.
- Develop the skills to build and troubleshoot Azure Data Factory pipelines with confidence.
- Enhance pipeline reliability by mastering the use of parameters to optimize your data workflows.
- Learn efficient methods for storing and structuring data using Azure Storage services.
- Understand the distinctive roles played by Azure Data Factory, Data Storage, SQL Server, and Data Bricks in the creation of an ELT solution.
Description
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 Should Attend!
- 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.