Category: Microsoft Fabric

Mastering Spark: Creating Resiliency with Retry Logic
Mastering Spark: Creating Resiliency with Retry Logic
Blog Posts

In any programming environment, handling unreliable processes—whether due to API rate limiting, network instability, or transient failures—can be a significant challenge. This is not exclusive to Spark but applies to distributed systems and programming languages across the board. In this post, we’ll focus on Python (since I’m a PySpark developer) and explore how to make… READ MORE

Navigating Power BI & Fabric Licensing
Navigating Power BI & Fabric Licensing
Blog Posts

Power BI licensing has certainly evolved over the years, and with so many changes, it’s no wonder questions keep coming up. Below are a few that I have heard and seen: I know, it’s a lot – but don’t worry. My goal with this blog is to tackle as much as I can. I have… READ MORE

How To Use Graph Semantics in Fabric
How To Use Graph Semantics in Fabric
How Tos

Use Graph Semantics in Fabric Henning Rauch shows viewers how to use graph semantics in #Microsoft #Fabric. Graph semantics in Kusto Query Language (#KQL) lets you query and model data as graphs. Henning demonstrates how a graph can be created to find out what happened at a specific time and what impact the anomalies would… READ MORE

Exploring Graph Semantics in Fabric Real Time Intelligence
Exploring Graph Semantics in Fabric Real Time Intelligence
Webinars

Exploring Graph Semantics in Fabric Real Time Intelligence Webinar Description: This session will cover the fundamental principles of graph theory, and the practical benefits of integrating these concepts into Fabric Real-Time intelligence. Participants will gain insights into the latest advancements in graph technology and explore real-world use cases demonstrating the impact on data analysis and decision-making… READ MORE

Microsoft Fabric reference architecture
Microsoft Fabric reference architecture
Blog Posts

Microsoft Fabric uses a data lakehouse architecture, which means it does not use a relational data warehouse (with its relational engine and relational storage) and instead uses only a data lake to store data. Data is stored in Delta lake format so that the data lake acquires relational data warehouse-like features (check out my book that goes into much detail… READ MORE