How does this skill handle data contracts?

It provides Python and YAML templates for defining schemas, validation rules, and evolution policies to ensure data remains reliable and backward-compatible.

Can I monitor data freshness with this skill?

Yes, it includes built-in patterns for checking freshness, completeness, and availability SLAs against your Databricks tables.

Is this skill compatible with Unity Catalog?

Absolutely, it includes patterns for persisting product metadata and governance controls directly into Unity Catalog for enterprise-wide discovery.

What is a data product in this context?

A data product is a self-contained, discoverable data asset with clear ownership, documented contracts, and guaranteed SLAs for consumer use.

Does it support Delta Live Tables (DLT)?

Yes, the skill provides specific implementation patterns for building data products using the DLT framework with integrated quality expectations.

Data Product Engineering

Name: Data Product Engineering
Author: vivekgana

byvivekgana

•

数据库管理

Implements robust data mesh architectures with standardized contracts, SLAs, and governance frameworks on Databricks.

This skill provides specialized patterns and implementations for building self-serve data platforms based on Data Mesh principles. It streamlines the creation of high-quality data products by offering templates for schema contracts, automated SLA monitoring for freshness and completeness, and centralized metadata management for discoverability. Ideal for organizations scaling data operations, it ensures clear ownership, versioned interfaces, and production-grade reliability for analytical assets by leveraging Databricks and Unity Catalog features.

主要功能

01Ready-to-use Delta Live Tables (DLT) implementation patterns

02Multi-layered governance patterns including PII classification and retention

032 GitHub stars

04Programmable SLA monitoring for data freshness, accuracy, and availability

05Automated data contract validation and schema evolution policies

06Standardized metadata registration for Unity Catalog discovery

使用场景

01Establishing clear data ownership and discoverable assets in an enterprise catalog

02Automating data quality checks and SLA enforcement for downstream consumers

03Scaling decentralized data architecture through Data Mesh implementation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add vivekgana/databricks-platform-marketplace data-products

For use in Claude.ai and ChatGPT

Download Skill