Explains Data Vault data modeling, its core components (Hubs, Links, Satellites), and the problems it solves for complex, evolving data sources.
Compares Star Schema and Snowflake Schema data models, explaining their structures, trade-offs, and when to use each for optimal data warehousing.
Explains dimensional modeling for analytics, covering facts, dimensions, grains, and table design for query performance.
Explains Slowly Changing Dimensions (SCD) types 1-3 for managing data history in data warehouses, with practical examples.
A technical analysis of missing features and wishlist for SQL Server Columnstore Indexes as of 2026, focusing on performance and functionality gaps.
Provides slides and SQL scripts from a 'Indexing for Dummies' session, focusing on SQL Server database performance.
An introduction to data warehousing concepts, covering architecture, components, and performance optimization for analytical workloads.
Explains the data lakehouse architecture, its layers (storage, table format, catalog, processing), and its advantages over traditional data warehouses.
An introduction to Data Vault modeling, a flexible data warehouse design method using Hubs, Links, and Satellites for scalable data integration.
Part 1 of a series on data warehouse transformation flows, building intuition for analytics engineers and data professionals.
An introduction to analytical data warehouses, explaining their purpose, differences from transactional databases, and their role in team-based analytics.
A data engineer explores the evolution of the data ecosystem, comparing past practices with modern tools and trends in 2022.
An introduction to modern data systems, explaining OLTP, OLAP, data warehouses, data lakes, and the roles of data engineers, analysts, and scientists.
Explores methods for copying data into Azure Synapse Analytics (SQL DW), focusing on the CTAS and new COPY INTO commands.
A technical guide on creating and managing Materialized Views in Azure SQL Data Warehouse, focusing on practical implementation and limitations.
Introduction to Materialized Views in Azure Synapse Analytics, explaining their purpose as a caching mechanism for data warehouse optimization.
Explores the availability and configuration of Columnstore Indexes across various Azure SQL Database tiers, including General Purpose, Serverless, and Hyperscale.
Announcement for a full-day workshop on SQL Server Columnstore Indexes at SQLSaturday Vienna 2020, covering practical techniques across multiple versions.
Explores compatibility of Columnstore Indexes with new features in SQL Server 2019, including Approximate Distinct Count and Scalar UDF Inlining.
Analyzes if Batch Mode on Rowstore eliminates the need for Columnstore Indexes in SQL Server, comparing performance and compression.
