Analytics Data Products

Our data ecosystems contain analytics data products that are essential to core business requirements and decisions. The data’s origin, impact path, quality, and freshness are all critical to the success of these products. The business decisions depends on the high quality aggregated data. The democratized access to metadata and the ability to consume it quickly to make informed decisions is profound. MeshLens makes it easy to integrate analytics data products into the Data Mesh view, providing deep insights into these products.

This tutorial illustrates how to integrate analytics data products with MeshLens. We start with a reference architecture that uses Glue workflow to update Glue catalog and run quality evaluation and emit aggregation results. We then perform metadata augmentation to integrate with MeshLens and view our catalog.

Here is a diagram of the reference analytics use case we start with and the Data Mesh entities, such as data products, domains, teams, and roles, that we view at the end of the tutorial:

Analytics Use Case:

MeshLens View:

You can see more details on Graph and table views here.

To run and see the results for analytics, refer to the onboarding use case here. The deployed stack will setup the resources and add MeshLens metadata augmentation. No other manual steps needed for this tutorial. If you want to follow step by step tutorial for metadata augmentation refer to ML Data Products or LLM Data Products tutorials.