1. How to Define Data As Product
Moving from "Data as Asset" to "Data as Product".
Core Characteristics (DATSIS)
2. Build Lifecycle & Team
The demanding engineering process and team needed to carry it out.
The Data Product Enablement Team
A strong data product is built by a cross-functional team and use the skill mis below to compare how each setup is staffed.
Role Focus:
Select a role to see details.
3. Evaluate Fit & Utility
Assess the product's Signal Validity and User Utility before proceeding with scaling.
Criterion 1: Signal Validity (Is the “Chocolate Bar” Real?)
When we combine multiple raw data points into an abstracted indicator (our “chocolate bar,” like Device Health), the first question is whether that abstraction represents something real and useful—not just a convenient aggregation. Can the recipe consistently separate meaningful underlying behavior from noise, seasonality, missing data, and sensor quirks, and does it hold up across different devices, environments, and time windows? A good signal is stable when nothing has changed, sensitive when something truly changes, explainable enough to build trust (“which ingredients drove the score?”), and verifiable against outcomes (failures, tickets, RMAs, customer complaints) so we can say the data-signal/data-product is actually good enough to depend on.
Criterion 2: User Utility
Does it solve a real problem? Select utility drivers.
Product Fit Assessment
According to the scores for Signal and Utility provided, the following recommendation is made.
ADJUST INPUTS
Interact with the tools above to get a strategic recommendation.
4. Validate & Readiness
Ensuring the product is Trustworthy, Consumable, and Discoverable before launch.
Trustworthy
Data accuracy, consistency, and reliability are ensured through SLA validations and automated quality testing.
Consumable
Products must be accompanied by explicit contracts, schemas, and documentation that have been verified through access tests.
Discoverable
The product's metadata and cataloging ensure easy discoverability, confirmed through catalog registration.
The Validation Lifecycle
Readiness Checklist
Quality Metrics
Data Product Visual Summary
Mindset, Lifecycle, and DATSIS at a glance
