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 analysis on their own …

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, materialized views, or …

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.

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

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 implementations on AWS are …

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 can be …

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.

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 typically …

Therefore, the blog focuses on how to deliver a data mesh based on SAP Datasphere. The goal of SAP Datasphere is to enable a business data fabric which can be leveraged in data mesh projects.

It describes a novel approach to Data Mesh called Streaming Data Mesh that deviates to quite some extent from the other tech stacks - and thus requires more in-depth explanations.