• What is the Data Outlier Analysis tab in Data Quality Lab (DQL)?

  This tab aims to help you identify potential data quality issues based on outlier data points. The score is calculated based on the proportion of data points that are moderate (2-3 standard deviations from the mean) and extreme outliers (3+ standard deviations from the mean). The higher proportion of outliers, the worse the score will be. Below this score explanation is a box plot which you can adjust using the geography filters, aggregation and time filters. The box plot surfaces facilitiesFew readers

• What is the Reporting Completeness tab in Data Quality Lab (DQL)?

  This tab has 2 goals. The explanation card at the top details how we assess reporting completeness and how it affects the score. The score is based on the consistency in the number of reports received per reporting period. The more consistent, the better it is for the score. This means a score can be provided even when the expected number of reports is unknown. The invesFew readers

• How do you access Data Quality Lab (DQL)?

  You can get to DQL in a few ways: You can get to DQL by clicking ‘Data Quality’ in the navigation bar at the top, then simply choose an indicator. There are also 2 ways to get data quality score within the Advanced Query Tool: Click the ‘Quality’ tab to the right of ‘Build Query’ - you’ll find a summary of data quality for the selected indicator and can click through to the full DQL page. Click on an indicator tag in the query form, under the ‘About’ tab, you’ll find the data quality scFew readers

• What is the objective of Data Quality Lab (DQL)?

  Effectively managing data quality is particularly important as electronic records and reports are not only heavily governed by strict regulation but also affect physical treatments and policies. They have a very real and tangible impact on people’s lives. Organizations must source quality data and build strong processes to manage it long-term in a conceptually structured manner. By doing so, they can expect to both speed up their existing processes and build learnings that allow for smarter polFew readers

• What is the Indicator Characteristics tab in Data Quality Lab (DQL)?

  This tab summarizes some basic facts about the indicator that may impact reporting or data quality, as well as explaining how they affect the score. After choosing an indicator, you’ll see cards displaying the indicator’s age, time since the last report, reporting completeness trend and estimated reporting periods. Both age and freshness are counted in terms of the number of estimated reporting periods (i.e. months if it’s a monthly report).Few readers