Data Products: It's not what you call them that matters. It’s what you do with them

The term "data product" was coined by DJ Patil in his book "Data Jujitsu." It refers to a reusable data asset that is independently usable by authorized consumers, and it has become more critical for businesses as they rely on it for analytics, AI, and data-driven software. However, the complexity of modern data stacks poses challenges for data and platform engineering teams, including proliferation of tools, integration overhead, pipeline fragility, and cost inefficiencies. To address these issues, unified orchestration and observability platforms are needed to provide an actionable view of the data product across every stage of the supply chain, allowing engineers to quickly identify problem areas and maintain the integrity and reliability of data pipelines.