Data Warehousing
Design and build a data warehouse with dbt, Snowflake, or BigQuery.
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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)
Simplifying Medallion Implementation with Materialized Views in Fabric | DEM566
→ Implement data warehouses with Materialized Views→ Optimize data transformations with Spark SQL
Integrate your data lake with Amazon Redshift for powerful insights (Hebrew)
→ Integrate Amazon Redshift with a data lake→ Run complex analytical queries
Start Building with Amazon Redshift's New Features - AWS Virtual Workshops
→ Build a petabyte-scale data warehouse with Amazon Redshift→ Run real-time analytics on data with Amazon Redshift
Transfer your Mainframe Data to GCP BigQuery using Google's Mainframe Connector
→ Transfer mainframe data to BigQuery→ Set up a data warehouse
Modernize Your Data Warehouse with Amazon Redshift - AWS Online Tech Talks
→ Design a scalable data warehouse with Amazon Redshift→ Run queries across large datasets
What's New with AWS Lake Formation: Securing and Governing Your Data Lake - AWS Online Tech Talks
→ Build and secure data lakes with AWS Lake Formation→ Optimize data governance with Governed Tables
How IHG Hotels modernize through a Teradata to BigQuery migration
→ Migrate data to cloud storage→ Optimize data analytics workflows
Analytics in 15: Build a Data Warehouse with Zero Infrastructure Management- AWS Analytics in 15
→ Launch Amazon Redshift Serverless→ Run high performant analytics workloads
Summit Live: Best Practices for Data Warehouse Migrations
→ Migrate legacy data warehouses→ Design reference architectures→ Implement data warehousing solutions
How to Build a Data Warehouse (Full Lifecycle Explained)
→ Build a data warehouse→ Design a data warehouse architecture→ Implement ETL pipelines
Read (6 articles)
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