Let's now look at one possible solution for the previous challenge:
Here are the scripts used to load raw data and transform it using Script activity:
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Have a deep dive into the foundational concepts and tools required to begin your journey with Microsoft Azure. You'll explore cloud computing basics, learn how to organize and manage resources efficiently using Azure Resource Groups, and set up core services like Blob Storage and Azure SQL Database. Additionally, you’ll secure sensitive data with Azure Key Vault and gain an overview of Azure Data Factory (ADF) to understand its role in modern data engineering workflows.
Explore the core functionalities of Azure Data Factory (ADF), a powerful tool for creating and automating ETL/ELT workflows. In this section, you'll learn how to configure services, datasets, and pipelines while exploring key activities such as Copy, Lookup, and Script. You'll also work with advanced features like the ForEach activity for iteration and pipeline parameters for flexibility.
This section focuses on leveraging Azure Data Factory's data flow capabilities to transform and enrich your data. You'll learn to connect various data sources, create derived columns, and merge datasets using joins. Practical examples will guide you through filtering, sorting, conditional splits, and aggregating data to generate meaningful insights. By mastering these transformations, you'll be equipped to build robust, efficient ETL workflows tailored to real-world data engineering challenges.
Apply your knowledge to real-world data engineering scenarios in this hands-on section. You'll tackle practical challenges like loading and analyzing data for different categories, identifying patterns, and assessing financial health using advanced ADF workflows. By solving these problems, you'll gain experience in designing end-to-end data solutions, working with diverse datasets, and generating actionable insights.