Going Further

This page is optional. Nothing here is required for Week 6's learning goals or the assignment. It collects deeper dives for students who finish the assignment early and want to explore more.

Full courses and tutorials

DataTalksClub Data Engineering Zoomcamp: a free, end-to-end course covering cloud data pipelines, containerization, orchestration, and warehousing. The cloud modules use GCP, but the patterns (object storage, managed databases, scheduled containers) are exactly what you practiced this week on Azure.
Microsoft Learn: Azure Fundamentals (AZ-900): the official learning path behind the AZ-900 certification. It covers cloud concepts, the Azure resource hierarchy, and core services in more depth than this week needed.

Deep dives on specific topics

Azure Key Vault overview: how Azure stores secrets centrally so your container never handles a raw connection string in production.
Infrastructure as Code with Bicep: the resource groups, storage accounts, and databases your teacher pre-created can be declared in code and re-created reproducibly. Bicep is Azure's native infrastructure-as-code language. This is a medior skill the track points at but does not require.
psql and DBeaver: the official DBeaver documentation, for going beyond the connect-and-query basics in Chapter 4: SQL editors, data export, and ER diagrams against your managed Postgres.
JMESPath tutorial: the query language behind az --query. Once you are filtering and reshaping JSON output from the az CLI, JMESPath turns long --output json dumps into exactly the fields you want.
PostgreSQL official documentation: the full reference for the database engine behind Azure Database for PostgreSQL. Useful when you need to look up a specific data type, function, or ON CONFLICT clause.
Python PostgreSQL tutorial with psycopg2: a comprehensive walk-through of CRUD operations, error handling, and transactions with psycopg2, going further than the connect-and-insert pattern in Chapter 4.

Community

DataTalksClub Slack and community: an active, free community of data engineers and analysts. The Slack has channels for the Data Engineering Zoomcamp, cloud questions, and the NL job market, and it is one of the better places to ask beginner cloud questions without judgment.

Books

Fundamentals of Data Engineering by Joe Reis and Matt Housley (O'Reilly): the standard conceptual reference for the field. The chapters on storage, ingestion, and the data engineering lifecycle frame why object storage, managed databases, and scheduled compute fit together the way Week 6 showed.
The Cloud Data Lake by Rukmani Gopalan (O'Reilly): a deeper read on object storage and data-lake architecture, useful once Blob Storage stops feeling like "just a folder in the cloud" and you want to understand layouts, formats, and access patterns at scale.

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