<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/05bbea0f573845238e3e151e555fd737&quot; frameborder=&quot;0&quot; width=&quot;1662&quot; height=&quot;1246&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1246</height><width>1662</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1246</thumbnail_height><thumbnail_width>1662</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/05bbea0f573845238e3e151e555fd737-773e297525844fd9.gif</thumbnail_url><duration>268.928</duration><title>How to Identify and Fix Data Errors</title><description>This Loom explains how to identify and fix errors across a dataset using both the UI and an error report. The example file has 45 errors across 54 records, and in the UI the view page shows spreadsheet rows with issues plus counts by error type, such as six rows with whitespace issues and 24 issues with inconsistent logic, which can be narrowed to specific columns. The Loom also covers using the error report for pass or fail counts and cell violations, and the scrubbing data log where hovering over cells reveals the exact issue and each row lists all issues. It notes three error categories, including warnings that should be verified and validated, and failed items marked as fail, with a comment section for communicating and resolving discrepancies.</description></oembed>