Webinar I Werner's Geospatial Revolution: Enhancing Fleet Safety with Advanced Spatial Analytics

Описание: Learn how Werner Enterprises transformed their logistics operations through advanced spatial analytics. By integrating Snowflake's AI Data Cloud and CARTO's Spatial Analytics Platform, Werner streamlined geospatial data processes, enabling real-time nationwide fleet monitoring amidst disastrous weather events.

In this webinar, Jeff Walters (Senior Director of Business Analytics at Werner) shares their journey from a siloed, inefficient data environment to a modern, cloud-native stack using Snowflake and CARTO. Discover how Werner's team developed a near real-time fleet monitoring dashboard that overlays live truck locations with weather alerts from NOAA. This solution replaced a slow, manual "tick sheet" process, enabling instant, data-driven decisions that prioritize driver safety and improve communication with customers during major weather events. The session also features insights from Fawad Qureshi (Field CTO at Snowflake) on the power of a unified data cloud.

In this session, you will learn:
00:00 - Welcome & Introductions
03:35 - Werner's Story: From One Truck to an Industry Leader
06:58 - The Challenge: Overcoming a Siloed Data Environment
09:16 - The Solution: Building a Cloud-Native Analytics Platform
12:38 - DEMO: The Real-Time Fleet & Weather Dashboard
18:12 - The Business Impact: Proactive Safety & Faster Decisions
19:53 - What's Next: The Future of AI and Embedded Analytics at Werner
25:42 - Snowflake's Perspective: Breaking Down Data Silos for Holistic Insights
29:43 - Live Q&A Session

Frequently Asked Questions (FAQ)
Q: What does the data infrastructure that supports this solution look like at Werner?
A: As Jeff explains at (32:35), Werner is moving to a formalized "data products" model within Snowflake. This involves classifying data into tiers, from a "gold standard" source of truth for core KPIs to near real-time data marts for operational use cases like the weather map, ensuring both reliability and agility.

Q: How is the live weather data integrated into the platform?
A: The weather data is pulled directly from NOAA. As mentioned at (20:55), CARTO helped build a workflow that connects to the NOAA data feed and updates it every 15-20 minutes, ensuring the map reflects current conditions.

Q: What are some good use cases for Generative AI with geospatial data?
A: As discussed from (37:09) onwards, GenAI is key to democratizing geospatial insights. It translates complex technical jargon (like "isochrone") into natural language ("walkability index"), making maps and analysis accessible to non-experts. This allows users to have a conversational interaction with their data, dramatically lowering the barrier to entry for spatial analysis.

Q: How quickly was this solution developed compared to legacy tools?
A: The speed of development was a major benefit. Jeff notes at (31:20) that building a similar solution in their old legacy GIS would have taken months and a large team. With CARTO and Snowflake, they had a working prototype with live weather data in just 3-4 days.

Resources Mentioned
CARTO & Snowflake: https://carto.com/snowflake/spatial-a...

Speakers on LinkedIn:
Jeff Walters (Werner):   / jeff-walters-9380a94  
Fawad Qureshi (Snowflake):   / qureshi  
Kirsten Mickow (CARTO):   / kirstenmickow  

Ready to start your own geospatial journey?
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