See Exactly When and Where Things Happen with a Timeline Filter
Animate any time-based dataset to spot patterns, track activity, and understand how your operations unfold hour by hour, day by day.
Problem
You've got timestamped data—deliveries, rides, incidents, asset movements—but static maps flatten everything into a single snapshot. You're left guessing when things happened, missing the rhythms and anomalies that only emerge over time. Exporting to spreadsheets or BI tools means losing the geographic context entirely.
Solution
Honeycomb Maps lets you filter and animate any dataset with date or timestamp fields. Drag a slider to focus on a specific moment, or hit play and watch your data move through time on the map. Patterns that were invisible in static reports—rush hour hotspots, weekend lulls, seasonal shifts—become immediately obvious.
Key Benefits
Spot patterns instantly
See how activity ebbs and flows across hours, days, or months. Identify your busiest corridors, your slowest periods, and everything in between—without writing a single query.
Investigate incidents in context
When something goes wrong, scrub back to the exact moment it happened. See what else was occurring nearby. Understand the sequence of events, not just the outcome.
Communicate with clarity
An animated map is worth a thousand slides. Share time-based visualizations with stakeholders who need to understand operational dynamics without digging through data.
Works with your existing data
Any Snowflake column with a date or timestamp type works automatically. No reformatting, no special preparation required.
How It Works
Example Use Case
A shared mobility company used the timeline filter to analyze e-bike rental patterns across a mid-sized city. By animating a week of trip data, they discovered that bikes were clustering in a downtown area by mid-morning and staying there—because riders weren't incentivized to return them to residential neighborhoods. The insight led to a rebalancing incentive program that improved bike availability by 35%.