Skills › Data Engineering

Data Warehousing

Design and build a data warehouse with dbt, Snowflake, or BigQuery.

intermediate 🔄 Data Engineering
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After this skill you can…

  • Model a star schema with dbt
  • Optimise BigQuery queries with partitioning and clustering
  • Implement data quality tests in dbt

Prerequisites

Watch (10 videos)

Introducing Lakehouse//RT and Reyden — Reynold Xin, Co–founder and Chief Architect
Databricks · beginner
→ Design a Lakehouse architecture→ Implement real-time analytics on governed data
Query S3 Data with SQL: Amazon Athena and AWS Glue Tutorial
Analytics Vidhya · beginner hands-on
→ Design a data warehouse on Amazon S3→ Use AWS Glue for data integration
Data Warehouse vs. Database: Which One Do You Need?
Coursera · beginner hands-on
→ Build data warehouses→ Optimize data storage→ Analyze data trends
Data Lake or Data Swamp?
AWS Developers · intermediate
→ Design Data Warehouses→ Implement Data Lakes→ Integrate Analytics Tools
Why AI GPU Servers Must Be Packed Into Dense Racks
Equinix · advanced
→ Manage data center infrastructure→ Implement efficient data storage solutions
Building reliable ETL pipelines with built-in observability - Data Engineering with Databricks
Databricks · advanced hands-on
→ Design data warehouses→ Implement data governance
Introducing Lakebridge: Free, Open Data Migration to Databricks SQL
Databricks · beginner hands-on
→ Design data warehouse architectures→ Implement data migration strategies
How to Build an Open Lakehouse: Best Practices for Interoperability
Databricks · beginner hands-on
→ Design a data lakehouse→ Implement cross-platform data access→ Unify data governance
Welcome Lakehouse, from a DWH transformation to a M&A data sharing
Databricks · intermediate hands-on
→ Transform data warehouse to cloud→ Implement data sharing between companies
Hybrid Lakehouses with Unity Governance, Local Execution and Egress Control
Databricks · advanced hands-on
→ Design Hybrid Lakehouses→ Implement Unity Governance→ Optimize Local Execution