Role of the Data Catalog in Data Mesh A Data Mesh is a decentralized architectural paradigm, while a Data Catalog is a tool or component used within it. A Data Mesh focuses on organizational principles like domain ownership and treating data as a product, whereas a Data Catalog provides a way to discover and inventory all the data assets, including these data products, across the decentralized domains. Essentially, data catalogs are foundational and necessary for a data mesh to function effectively by providing a central point of access and discovery for decentralized data

Incremental refresh is a feature in Power BI that allows you to increase efficiency when refreshing data by only updating the most recent data instead of completely rewriting the entire dataset. This is especially useful for large datasets as it minimizes the amount of data handled during the refresh process, reducing load times and resource usage.

This document goes over how to write code to package up and promote a TEST environment Azure Data Factory to PROD environment Data Factory using Linked ARM Templates via a new Linked Template Specs process. Linked Templates are needed when your Data Factory size is over 4MB. This process goes over how to deploy large Data Factories.

Python is an object-oriented programming language, and it supports the four main pillars of OOP: encapsulation, inheritance, polymorphism, and abstraction.

Orchard Core doesn't render HTML directly, but instead will usually render something called a Shape, which is an object that represents the thing to render and has all the necessary data and metadata to render HTML. When rendering a Shape, Orchard Core will look for specific templates, passing the Shape to this template. Orchard Core can match with many templates for the same Shape. These potential templates are called Alternates.