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We will also be introducing a timeline view of assertion failures over a given time period. Our hope is to make it even easier to detect trends in data quality failures at a single glance.</p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="personalizing-the-dashboard">Personalizing the Dashboard<a href="#personalizing-the-dashboard" class="hash-link" aria-label="Direct link to Personalizing the Dashboard" title="Direct link to Personalizing the Dashboard"></a></h2><p>We understand that each team, and perhaps even an individual may care about a different subset of data than others.
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For this reason, we have included a broad range of filters to make it easy to drill down the Dashboard to the specific subset of data you care about. You can filter by:</p><ol><li>Dataset Owner</li><li>Dataset Domain</li><li>Dataset Tags
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...and much more.</li></ol><p>In addition, both the <code>By Tables</code> tab and the <code>Incidents</code> tab will apply your global <code>View</code> (managed via the search bar on the very top of DataHub's navigation). So if you already have a view created for your team, these tabs will automatically filter the reports down to the subset of data only you care about.</p><p align="left"><img loading="lazy" width="80%" src="https://raw.githubusercontent.com/datahub-project/static-assets/main/imgs/observe/data-health/view-applied.png" class="img_ev3q"></p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="bulk-create-smart-assertions">Bulk Create Smart Assertions<a href="#bulk-create-smart-assertions" class="hash-link" aria-label="Direct link to Bulk Create Smart Assertions" title="Direct link to Bulk Create Smart Assertions"></a></h2><p><a href="/docs/managed-datahub/observe/smart-assertions">Smart Assertions</a> are AI Anomaly Checks that can be used to quickly 'strap a seatbelt' across your data landscape. You can hit the 'Bulk Create' button in the top right corner of the data health dashboard to quickly set up anomaly detection across your most important assets:</p><div align="center"><iframe width="560" height="315" src="https://www.loom.com/embed/f6720541914645aab6b28cdff8695d9f?sid=58dff84d-bb88-4f02-b814-17fb4986ad1f" frameborder="0"></iframe></div></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="slackUtm_uoBr"><div class="slackUtm_uoBr"><hr>Need more help? Join the conversation in <a href="https://datahub.com/slack?utm_source=docs&utm_medium=footer&utm_campaign=docs_footer&utm_content=docs/managed-datahub/observe/data-health-dashboard">Slack!</a></div></div><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/datahub-project/datahub/blob/master/docs/managed-datahub/observe/data-health-dashboard.md" target="_blank" rel="noreferrer noopener" class="theme-edit-this-page"><svg fill="currentColor" height="20" width="20" viewBox="0 0 40 40" class="iconEdit_Z9Sw" aria-hidden="true"><g><path d="m34.5 11.7l-3 3.1-6.3-6.3 3.1-3q0.5-0.5 1.2-0.5t1.1 0.5l3.9 3.9q0.5 0.4 0.5 1.1t-0.5 1.2z m-29.5 17.1l18.4-18.5 6.3 6.3-18.4 18.4h-6.3v-6.2z"></path></g></svg>Edit this page</a></div><div class="col lastUpdated_VsjB"></div></div></footer><div class="feedbackWrapper_mUHF"><div class="feedbackWidget_PX4d"><div class="feedbackButtons_wn3V"><strong>Is this page helpful?</strong><div><button class="feedbackButton_UgQs"><span role="img" aria-label="like" class="anticon anticon-like"><svg viewBox="64 64 896 896" focusable="false" data-icon="like" width="1em" height="1em" fill="currentColor" aria-hidden="true"><path d="M885.9 533.7c16.8-22.2 26.1-49.4 26.1-77.7 0-44.9-25.1-87.4-65.5-111.1a67.67 67.67 0 00-34.3-9.3H572.4l6-122.9c1.4-29.7-9.1-57.9-29.5-79.4A106.62 106.62 0 00471 99.9c-52 0-98 35-111.8 85.1l-85.9 311H144c-17.7 0-32 14.3-32 32v364c0 17.7 14.3 32 32 32h601.3c9.2 0 18.2-1.8 26.5-5.4 47.6-20.3 78.3-66.8 78.3-118.4 0-12.6-1.8-25-5.4-37 16.8-22.2 26.1-49.4 26.1-77.7 0-12.6-1.8-25-5.4-37 16.8-22.2 26.1-49.4 26.1-77.7-.2-12.6-2-25.1-5.6-37.1zM184 852V568h81v284h-81zm636.4-353l-21.9 19 13.9 25.4a56.2 56.2 0 016.9 27.3c0 16.5-7.2 32.2-19.6 43l-21.9 19 13.9 25.4a56.2 56.2 0 016.9 27.3c0 16.5-7.2 32.2-19.6 43l-21.9 19 13.9 25.4a56.2 56.2 0 016.9 27.3c0 22.4-13.2 42.6-33.6 51.8H329V564.8l99.5-360.5a44.1 44.1 0 0142.2-32.3c7.6 0 15.1 2.2 21.1 6.7 9.9 7.4 15.2 18.6 14.6 30.5l-9.6 198.4h314.4C829 418.5 840 436.9 840 456c0 16.5-7.2 32.1-19.6 43z"></path></svg></span></button><button class="feedbackButton_UgQs"><span role="img" aria-label="dislike" class="anticon anticon-dislike"><svg viewBox="64 64 896 896" focusable="false" data-icon="dislike" width="1em" height="1em" fill="currentColor" aria-hidden="true"><path d="M885.9 490.3c3.6-12 5.4-24.4 5.4-37 0-28.3-9.3-55.5-26.1-77.7 3.6-12 5.4-24.4 5.4-37 0-28.3-9.3-55.5-26.1-77.7 3.6-12 5.4-24.4 5.4-37 0-51.6-30.7-98.1-78.3-118.4a66.1 66.1 0 00-26.5-5.4H144c-17.7 0-32 14.3-32 32v364c0 17.7 14.3
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