Simplifying Multi-Company Data Consolidation with Medallion Architecture in Microsoft Fabric
Managing data across multiple subsidiaries can feel like juggling different systems, formats, and rules all while leadership demands one unified view. In this blog, I’ll show you how Microsoft Fabric’s Medallion Architecture (Bronze–Silver–Gold) turns that chaos into clarity. Learn how to standardize, consolidate, and scale your multi-company data effortlessly using Fabric Lakehouse and Warehouse from raw ingestion to business-ready insights. 💡If your organization is struggling to unify data across multiple entities, this guide will show you a proven architectural blueprint that actually works.An Overview of Lakehouses and Data Warehouses
Unlocking the Future of Data: Lakehouses vs. Data Warehouses In today’s data-driven world, choosing the right architecture is crucial for turning information into insight. Are traditional data warehouses still the gold standard, or are modern lakehouses rewriting the rules? Dive into our latest article as we explore how these two powerful approaches stack up — and discover which one could transform your data strategy.
# Top 10 Anti-Patterns in Fabric Warehouse Production Code Part -2
You fixed the loops, batched the loads, and listed your columns explicitly. Good. But your Fabric Warehouse still has hidden cost leaks. In Part 2, we tackle the six anti-patterns that don't show up until your tables are large and your team is shipping fast: scalar UDFs that silently dodge Fabric's inlining engine, MERGE statements that join on the wrong column (and why case-sensitivity makes it worse), small-file fragmentation from over-partitioned lakehouse shortcuts — and the OPTIMIZE + VACUUM + V-Order trio that fixes it — plus three CI/CD habits (missing column lists, hardcoded workspace GUIDs, and DROP-recreate cycles) that quietly erase your statistics, your permissions, and your Monday morning peace of mind. Ten anti-patterns. Two posts. One rule: Fabric Warehouse is not SQL Server.# Top 10 Anti-Patterns in Fabric Warehouse Production Code
With Microsoft Fabric Warehouse , many teams carried over habits from dedicated SQL pools, Synapse serverless, or on-premises SQL Server. Most of those habits still work — but a handful of them quietly erode performance on Fabric's Delta Parquet + MPP engine, and they only reveal themselves once your tables cross a few hundred million rows or your capacity starts throttling. What looks like a "Fabric is slow" problem is, more often than not, a code problem inherited from an older architecture. Over the last several months I've reviewed a number of production Fabric Warehouses across industries, and the same anti-patterns keep showing up. In this first post of a two-part series, I'll walk through the four that cost teams the most Capacity Units and the most debugging time, show the fix for each, and — most importantly — explain why the fix matters specifically in Fabric, not just as a generic SQL best practice. Part 2 will cover the remaining six.The Importance of New Case-Insensitive Collation in Fabric Warehouse
The Fabric Warehouse service, launched in summer 2023, simplifies end-to-end data and analytics solutions. This T-SQL based platform provides SQL developers with a dedicated Data Warehousing environment featuring auto-scale and fault-tolerance capabilities. It uses the Parquet file format and Delta Lake, which offer new possibilities in Data Warehousing. This blog post will discuss the new case insensitive collation feature.
