# How to Build Data Quality Scorecards That Support Adoption and Trust

DevFeed: [How to Build Data Quality Scorecards That Support Adoption and Trust](<https://devfeed.tech/articles/most-data-quality-initiatives-fail-before-they-start-here-s-why-83008.md>)

Original publisher: [Read original article](<https://montecarlo.ai/blog-data-quality-scorecard-data-quality-initiative>)

Author: Barr Moses

Published: 2024-07-20T00:53:20Z

Content type: article

Language: en

Sources: [Monte Carlo](<https://devfeed.tech/sources/monte-carlo.md>)

Topics: [Data Quality](<https://devfeed.tech/topics/data-quality.md>), [Data Management](<https://devfeed.tech/topics/data-management.md>), [data observability](<https://devfeed.tech/topics/data-observability.md>), [Data Space](<https://devfeed.tech/topics/data-space.md>)

Tags: [bad-data](<https://devfeed.tech/tags/bad-data.md>), [data-catalog](<https://devfeed.tech/tags/data-catalog.md>), [data-engineering](<https://devfeed.tech/tags/data-engineering.md>), [data-management](<https://devfeed.tech/tags/data-management.md>), [data-observability](<https://devfeed.tech/tags/data-observability.md>), [data-quality](<https://devfeed.tech/tags/data-quality.md>), [data-quality-initiative](<https://devfeed.tech/tags/data-quality-initiative.md>), [data-quality-standards](<https://devfeed.tech/tags/data-quality-standards.md>), [quality](<https://devfeed.tech/tags/quality.md>)

## AI overview

The article recommends building data quality scorecards around business priorities, measurable data health, and incentives that encourage teams to produce and use reliable data. It highlights factors such as usability, stewardship, documentation, lineage, monitoring, freshness, schema changes, ownership, and incident response. It also advocates for automating evaluation and discovery through data observability tools and data catalogs.

## Source excerpt

Show me your data quality scorecard and I'll tell you whether you will be successful a year from now.