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)

Star Schemas & Track Changes
Coursera · advanced hands-on
→ Design a data warehouse→ Optimize dimensional models
Build A Data Warehouse in Azure
Coursera · intermediate hands-on
→ Build a data warehouse in Azure→ Implement data warehousing fundamentals
Building Data Lakes and Lakehouses with Microsoft Fabric
Coursera · intermediate hands-on
→ Design a Lakehouse with Delta tables→ Implement medallion architecture patterns
Build a Data Warehouse in AWS
Coursera · intermediate hands-on
→ Build a data warehouse in AWS→ Optimize data warehouse performance
Simplifying Medallion Implementation with Materialized Views in Fabric | DEM566
Microsoft Developer · intermediate hands-on
→ Implement data warehouses with Materialized Views→ Optimize data transformations with Spark SQL
Integrate your data lake with Amazon Redshift for powerful insights (Hebrew)
AWS Developers · intermediate hands-on
→ Integrate Amazon Redshift with a data lake→ Run complex analytical queries
Microsoft Azure - Data Lake
Coursera · advanced hands-on
→ Design a data analytics solution with Azure Data Lake→ Optimize data storage and job submission with U-SQL
Ultimate AWS Data Engineering Bootcamp - 15 Real-World Labs
Coursera · intermediate hands-on
→ Design data warehouses with Redshift→ Implement data pipelines with AWS
Start Building with Amazon Redshift's New Features - AWS Virtual Workshops
AWS Developers · intermediate hands-on
→ Build a petabyte-scale data warehouse with Amazon Redshift→ Run real-time analytics on data with Amazon Redshift
Creating Permanent Tables and Access-Controlled Views in BigQuery
Coursera · intermediate hands-on
→ Create permanent tables in BigQuery→ Design access-controlled views