This is the core idea behind the data mesh concept: Domain-oriented decentralization for analytical data. A data mesh architecture enables domain teams to perform cross-domain data …

dbt is a framework to transform, clean, and aggregate data within your data warehouse. Transformations are written as plain SQL statements and result in models that are SQL views, …

Microsoft offers Azure Synapse Analytics, along with both Data Lake Storage Gen2 and SQL database, as the central components for implementing a data mesh architecture.

But is it also a good choice for a general Data Mesh platform? Let's dive into the components that we would use for Data Mesh. The starting point in Databricks is the workspace. Each team …

We often see Data Mesh implementations relying on AWS S3 and AWS Athena as the primary means to share and query data products. Interestingly enough, most data mesh …

Overview and comparison of current big data architectures: Logical data warehouse, Data fabric, Data mesh Goal: Provide guidance in choosing the right architecture

Each node in a data mesh is called data product. Every data product exists within a bounded context and one bounded context might contain several data products.

Apr 3, 2024 · In this article, we will use Data Contracts and the new Databricks Asset Bundles that are a great fit to implement data products. All source code of this example project is available …

Design a single use case or the whole data mesh using the Data Mesh Canvas. Have a look at the definitions of source-aligned, aggregate, or consumer-aligned data products.

The available offerings of cloud providers already provide a sufficient set of good self-serve data services to let you form a data platform for your data mesh. We want to show which services …