Slowly Changing Dimensions Without Corrupting Your Facts
Should last year's revenue move when a customer changes segment? Pick an SCD type per column, write a replay-safe Type 2 MERGE, and join facts correctly.
42 articles
Should last year's revenue move when a customer changes segment? Pick an SCD type per column, write a replay-safe Type 2 MERGE, and join facts correctly.
DiskANN vector indexes are now GA in Azure SQL and Fabric SQL. When embeddings belong next to your rows, and when Azure AI Search still wins.
Grain is what one row of a table means. Most wrong numbers come from a join or aggregation that quietly changed it. How to declare grain and test it.
Snowflake Cortex makes AI accessible through familiar SQL without data movement.
Text-to-SQL democratizes data access by enabling natural language queries.
Fabric Databases bring operational database workloads into the unified Fabric platform, with automatic integration to OneLake.
1. Filter early : Push filters as close to data source as possible 2. Use appropriate joins : Broadcast small tables 3. Enable AQE : Adaptive Query…
Copilot for SQL transforms natural language into T-SQL queries. Today I'm exploring how to leverage AI for data warehouse development in Fabric.
The aiquery() function enables custom LLM interactions directly in SQL. Unlike specialized functions, it allows you to craft any prompt and get intelligent…
Databricks SQL AI functions bring large language model capabilities directly into SQL queries. Process text, generate insights, and enrich data without…
Natural language to SQL (NL2SQL) transforms how users interact with databases. This guide covers implementation strategies, from simple approaches to…
Query performance is where UX and cost meet. My practical approach is to measure user-facing latency, inspect query plans, and prioritise optimisations that…
Tomorrow we'll explore Query Insights for monitoring and optimization. Cross Database Queries OneLake Shortcuts Security Model
If you're coming to Fabric Warehouse from a SQL Server or Azure SQL Database background, the T-SQL compatibility is reassuring — CTEs, window functions…
LLM-powered SQL generation democratizes data access. With proper validation and safety measures, it enables anyone to query databases using natural language.
The query editor in Azure Data Studio provides everything needed for efficient SQL development.
Azure Data Studio offers a lightweight, customizable interface that combines the best features of modern code editors with database-specific functionality.
MySQL 8.0 features significantly enhance your application capabilities on Azure Database for MySQL Flexible Server.
Databricks SQL offers: SQL Endpoints : Serverless compute for SQL queries Query Editor : Web based SQL IDE Dashboards : Built in visualization and reporting…
These optimizations can dramatically improve dedicated SQL pool performance while reducing resource consumption.
Arc-enabled data services bring cloud-native database capabilities to any environment. Whether you need SQL Server or PostgreSQL, you can run managed…
Synapse Dedicated SQL Pool (formerly Azure SQL Data Warehouse) is the massively parallel processing (MPP) engine for structured, petabyte-scale analytical…
Synapse Serverless SQL Pool is the query engine that turned Azure Data Lake into an ad-hoc analytics platform—you write T-SQL, point it at files in ADLS…
The Stored Procedure Activity bridges the gap between data movement and data transformation, enabling complex database logic to be orchestrated as part of…
Azure SQL's Automatic Tuning is the machine learning system that acts on Query Store data to make index and query plan decisions that would otherwise…
Query Store transforms database performance troubleshooting from guesswork into data-driven analysis, making it an indispensable tool for maintaining…
IQP represents a significant step toward self-tuning databases, reducing the manual effort required to optimize query performance while automatically…
Serverless is perfect for dev/test environments, infrequently used applications, and workloads with predictable quiet periods. For consistent…
The key benefit of elastic pools is resource sharing. If you have 100 databases that each spike at different times, you don't need to provision for 100…
Traditional database architectures couple compute and storage tightly together. Hyperscale breaks this coupling by introducing a distributed storage…
Databricks SQL Analytics provides: Native SQL interface to query Delta Lake tables SQL Endpoints with auto scaling compute Built in visualization and…
Azure SQL Managed Instance is the SQL Server target I recommend most for lift-and-shift migrations from on-premises SQL Server. It's PaaS—no OS to patch…
Arc data services let you run Azure-managed databases on your own infrastructure while using Azure tools for management.
Dedicated SQL pools distribute data across 60 distributions for parallel processing: Control node : Orchestrates queries and manages metadata Compute nodes…
SQL Analytics on Azure Databricks is in public preview. Here is what it is, how to pilot it properly, and when Synapse or Power BI alone is the better fit.
How I'd structure Synapse serverless SQL now it's GA: a user database, credentials, views over the lake, CETAS, and habits that keep the per-TB bill small.
How to make tampering detectable in Azure SQL Database with temporal tables, a T-SQL hash chain, auditing, and immutable blob storage.
There's a moment in any growing SaaS where someone runs spspaceused and the room goes quiet—the database is approaching the 4 TB ceiling and the migration…
Note: While dedicated SQL pools are mature (evolved from Azure SQL DW), the Synapse unified experience is still in preview.
Encrypt sensitive columns—keys never exposed to SQL Server. Azure SQL security is comprehensive—use all layers for maximum protection.
A second Synapse-preview note, on what I think is the genuinely new idea in the platform: serverless SQL. Point T-SQL at parquet, CSV, or JSON in your data…
How to size an Azure SQL Database elastic pool for database-per-tenant SaaS, measure tenant load first, and spot the workloads where pooling costs more.