--- title: Data can be accurate and complete and poor quality description: Understand why data accuracy and completeness alone don't guarantee high-quality data for your specific context and purpose. Relevance is key. image: https://riskinsights.com.au/hubfs/Data%20can%20be%20accurate%20and%20complete%20and%20poor%20quality.png --- [Skip to content](https://riskinsights.com.au/blog/data-can-be-accurate-and-complete-and-poor-quality#main-content) [![Risk Insights - Logo - (RGB, Horizontal, Small)](https://riskinsights.com.au/hs-fs/hubfs/Risk%20Insights%20-%20Logo%20-%20(RGB%2c%20Horizontal%2c%20Small).png?width=200&height=40&name=Risk%20Insights%20-%20Logo%20-%20(RGB%2c%20Horizontal%2c%20Small).png)](https://riskinsights.com.au) - [Articles](https://riskinsights.com.au/blog) - [Approach](https://riskinsights.com.au/approach) Show submenu for Approach - [Commissions (Accuracy)](https://riskinsights.com.au/broker-partner-commission-accuracy-reviews) - [Claims Fraud (Fairness)](https://riskinsights.com.au/claims-fraud-fairness-reviews) - [Fees and Charges (Accuracy)](https://riskinsights.com.au/fee-and-charge-accuracy-reviews-risk-insights) - [About](https://riskinsights.com.au/about) - [Contact](https://riskinsights.com.au/contact) Open main navigation Close main navigation - [Articles](https://riskinsights.com.au/blog) - [Approach](https://riskinsights.com.au/approach) Show submenu for Approach - [Commissions (Accuracy)](https://riskinsights.com.au/broker-partner-commission-accuracy-reviews) - [Claims Fraud (Fairness)](https://riskinsights.com.au/claims-fraud-fairness-reviews) - [Fees and Charges (Accuracy)](https://riskinsights.com.au/fee-and-charge-accuracy-reviews-risk-insights) - [About](https://riskinsights.com.au/about) - [Contact](https://riskinsights.com.au/contact) --- 27 Nov 2025 # Data can be accurate and complete and poor quality ![Picture of Yusuf Moolla](https://riskinsights.com.au/hs-fs/hubfs/Yusuf_Moolla_Headshot-transformed.png?width=50&name=Yusuf_Moolla_Headshot-transformed.png) [Yusuf Moolla](https://riskinsights.com.au/blog/author/yusuf) Share: [linkedin-in icon](http://www.linkedin.com/shareArticle?mini=true&url=https://riskinsights.com.au/blog/data-can-be-accurate-and-complete-and-poor-quality) [envelope icon](mailto:?body=https://riskinsights.com.au/blog/data-can-be-accurate-and-complete-and-poor-quality) **TL;DR** • Data can be accurate and complete, but still irrelevant and low quality (for our purpose). • Many DQ metrics focus on technical measures, not what really matters for the context.   In the right context, completeness and accuracy are key data quality indicators. Data quality has various definitions. Many of them focus on completeness and accuracy. So DQ metrics often focus just on whether data is complete and accurate. But if we use data that is not relevant to our context, these metrics don’t matter. The data might be 100% accurate and 100% complete, but still meaningless. This means that, in the context of our use case, the data isn’t actually high quality for what we need. When deciding how to measure data quality, the first question should really be “Is this data fit for our purpose?”   ## Examples in practice 1. **External demographic data** from third parties like Experian. We explored this in [this article about causation](https://riskinsights.com.au/blog/more-data-more-correlations-but-is-it-causation) and [this article about gender data](https://riskinsights.com.au/blog/finding-sex-gender-in-data). These might be useful for certain marketing activities, but we should not be using them to price risk, approve loans or adjudicate claims. Even if a data provider reports “high quality”, it’s not relevant to our context and is therefore poor quality for our purpose. 2. **Internal data that is not relevant** to our use case. We explored driver’s license type in [this article about the direct monetary impact of bias](https://riskinsights.com.au/blog/bias-monetary-impact). In cases like these, the data might be accurate, but not relevant. In fact, making it less “accurate” could actually make it higher quality for our purpose.   Dedicated data quality or governance teams may not spot the difference. Context matters, and this often means that input from subject matter experts is needed. You can’t completely outsource your DQ responsibilities to a central team.   --- Disclaimer: The info in this article is not legal advice. It may not be relevant to your circumstances. It was written for specific contexts within banks and insurers, may not apply to other contexts, and may not be relevant to other types of organisations. ---     ## Related posts [![Lego people of different types - Photo by Jason Leung on Unsplash](https://riskinsights.com.au/hs-fs/hubfs/Lego_people%20(Medium).jpg?height=200&name=Lego_people%20(Medium).jpg)](https://riskinsights.com.au/blog/finding-sex-gender-in-data) ## [Finding Sex/Gender in FS Data](https://riskinsights.com.au/blog/finding-sex-gender-in-data) 03 Jul 2025 TL;DR • Sex has eight key attributes, some direct in data, but mostly inferred. • Many attributes... 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[Read more](https://riskinsights.com.au/blog/finding-disability-in-data) [![Checking data for a review: part 1 (overview)](https://riskinsights.com.au/hs-fs/hubfs/checking-data-part-1.png?height=200&name=checking-data-part-1.png)](https://riskinsights.com.au/blog/the-checks-we-run-before-using-data-for-a-review-part-1) ## [The checks we run before using data for a review](https://riskinsights.com.au/blog/the-checks-we-run-before-using-data-for-a-review-part-1) 08 Oct 2026 TL;DR • Before we use data for a review, we run a set of checks on a sample, then repeat most of... [Read more](https://riskinsights.com.au/blog/the-checks-we-run-before-using-data-for-a-review-part-1) We acknowledge Aboriginal and Torres Strait Islander peoples as the Traditional Custodians of the lands on which we live and work. We pay our respects to Elders past and present, and honour the rich diversity of the world's oldest living cultures. 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