Using Dashboard Filtering to Get Customer Usage in Seconds from TBs of Data
Bronto has introduced a new dashboard filtering feature that allows users to quickly analyze customer usage data from large datasets. This feature enables real-time updates across all widgets in a dashboard using SQL queries, streamlining the process of gathering insights. The ability to filter data without prior configuration enhances productivity and allows for deeper investigation of trends and patterns.
- ▪Bronto's new dashboard filtering feature allows for simultaneous updates across all widgets using SQL queries.
- ▪Users can analyze trends over extended periods, with a default data retention of one year.
- ▪The filtering process does not require initial configuration of keys, making it user-friendly and efficient.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3933240) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Patrick Londa for Bronto Posted on May 22 • Originally published at bronto.io Using Dashboard Filtering to Get Customer Usage in Seconds from TBs of Data #logging #devops #observability #productivity Authored by Conall Heffernan As the Customer Success lead at Bronto, I need fast, reliable insights into customer health and product usage — but I don't have time to constantly update indexes, schemas, or individual widgets just to answer new questions.
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