In this article, we'll explore the fascinating intersection of supply chains and graph databases. We'll explore the intricacies of supply chains, understand their complexities, and explore the practical benefits of utilizing graph databases for modeling and optimizing these networks.
In Part 2 of our series, we explore the practical aspects of enabling SQL Graph for modeling supply chains, including creating tables for nodes and edges and inserting data into them. We also introduce the MATCH keyword for querying graph data, simplifying the retrieval of information based on relationships between entities.
In Part 3 of our series, we delve into the rewards that graph databases bring to supply chain modeling. We explore the clarity achieved through the MATCH keyword, enabling precise communication between technical and business teams. Validation becomes seamless as stakeholders intuitively analyze the graph, uncovering missing relationships and enrich...
In Part 4 of our series, we explore the power of graph visualization in understanding and analyzing supply chain data. Using tools like PowerBI and the force-directed graph visual, we transform our SQL Graph data into an interactive and shareable format. The visualization allows us to easily comprehend the relationships within the supply chain, mak...
Building on my first Azure SQL Bindings blog post and taking inspiration from Drew Skwiers-Koballa's post on SQL Bindings, we are going to create a change data stream with Azure SQL Database. Now, usually, the first part of these blogs is a prerequisite section that goes over what you need to install locally to get started. From talking to many of ...
The Azure SQL Database has two main ways to track changes with data (rows/DML) as well as table changes. One of those methods is Change Tracking with the other being Change Data Capture. Today’s post will be going into depth on Change Tracking. Change Tracking and Change Data Capture So, what’s the difference between the two? Change Data Capture ...
