CoreLogic is a premier property and location intelligence provider. The talk will spotlight how a combination of deep property and location insights, combined with CARTO's platform on a cloud-first approach, help produce some of CoreLogic's innovative solutions that are creating an impact across many industries.

Collaborative logistics allows two independent organizations to find spatial overlap in their customers without sharing any private personal information. Join this session, where we will define a spatial data clean room and its importance for collaborative logistics as well as finding optimal locations, and Smart City use cases. We will share the architecture that makes this possible and show live demo showcasing collaborative logistics for the city of Austin, TX using geospatial SQL functions, routing optimization and geospatial visualizations.

We will discuss how disparate data related to community characteristics, health outcomes/utilization, and access to resources can be analyzed together to identify population health needs across diverse communities and enable strategic deployment of solutions to address local social and access barriers associated with key health outcomes and utilization patterns. We will provide examples of how these data have been leveraged to identify COVID-19 resource needs and deploy transportation services to members residing in resource constrained regions.

How did the Cloud change how we work with data? What does that tell us about GenAI and LLMs? What does serverless have to do with all of this? How will event-based architectures drive AI-powered applications of the future?

Dive into the success story of NCM and Echo Analytics: Revolutionising in-theatre advertising using geospatial insights. Explore how this partnership harnessed the power of geospatial data to redefine audience targeting, ad optimization, and elevate experiences beyond the cinema.

Geographically weighted regression combined with spatial regression can predict the rent prices of ground floor retail space. Without these techniques, regression models ignore spatial autocorrelation and result in overestimation or underestimation of prices. Using R spatial statistics packages, it is possible to automate the selection of variables to predict price. Is it better to incorporate rents at nearby properties within a radius or walking distance? Should you incorporate population density or the presence of certain co-tenants? Automation loops through all combinations, creates local neighborhoods, and selects the optimal GWR and spatial regression models to answer these questions.

Revel's mission is to accelerate EV adoption by providing the infrastructure and services that make it easy to go electric. Join Will Geary, Senior Data Scientist at Revel, as he delves into how to build an electric rideshare service from the ground up using spatial data science.

In the world of out of home advertising, the quest for selecting impactful placements and accurate campaign measurement has long been challenged by the scarcity of dependable data. Join Eugene, Senior Product Manager from SafeGraph, and Chen, Sciences Director from Billups, as they delve into the art of campaign planning and precisely measuring campaign performance through the lens of POI data and building footprints.

When it comes to finding new markets and growing market share, the key to success is somewhere in your customer data. Get a first-hand look at how brands can apply customer-level predictions to broader populations in order to assess new market opportunities and develop powerful geomarketing strategies.

Join experts across the geospatial industry to hear their thoughts on careers and skills in Spatial Data Science. What makes hiring in this industry such a challenge? Is there a skills gap, and what can we do to change this? Hear all this and more, and make sure to bring along your most burning questions!

In cities, geographic data scientists have access to vast data from multiple sources. Despite such abundance of data, short of compiling them into a huge multivariate atlas, turning these into information remains a significant challenge.  In this paper, we present a solution that pairs old technology (unsupervised learning) with new technology (LLMs and in-context learning) to product an open and reproducible geodemographic classification system for the United States.  We demonstrate a hierarchical prompting strategy with in context learning to summarize highly multivariate cluster analyses.  Our map is carefully validated and useful both as demonstration of a new technique and as a better way to understand block groups in the United States.

Google Maps Platform recently launched 3D visualization and introduced a new suite of products for the environment. We are expanding what developers can do with Google Maps Platform to build new experiences and pave the way for a sustainable future with the Solar API, Air Quality API and Pollen API.  Additionally, the 3D Map Tiles API opens up new data visualization possibilities.  Learn how you can go beyond the map with Google Maps Platform's newest product announcements and innovations.

Global health delivery continues to be one of the greatest challenges to our worldcommunity, with over 400 million of the world's population lacking access to basic medicalcare and 5 billion to safe and affordable surgical care. Yet, recent developments in datascience are presenting an unprecedented opportunity to unlock access to critical care bycreating efficient markets in healthcare delivery. Learn how Virtue Foundation, with.Partners such as Carto, are using ML/AI to predict medical deserts and get criticalhealthcare to those who need it most.

Join Ricardo to discover how satellite imagery is helping to uncover the impact of wildfires on UK emissions. Despite not being commonly associated with wildfires, the UK has recently witnessed a surge in incidents. As compilers of the UK National Atmospheric Emissions Inventory, we've developed a fire detection algorithm to monitor these events and their emissions. During this talk, we will guide you through our methodology and explore how a modular approach allows this pipeline to go beyond fires to monitor algal blooms, deforestation, and glacial changes.

A team of geospatial data scientists had developed deep, multi-source intelligence for their branches.  They acted on the insights to create positive outcomes from seasonal challenges and created predictive models for the year ahead.  More recently, they've upped their game embracing near real time spatiotemporal data to take decision-making to a whole new level.   Whilst we can't disclose the organization, we can share the case study and demonstrate their prowess in urban movement analysis.  You'll see how they've been able to set up alerts and alter the position of their mobile units on an hourly basis to delight loyal customers and be in the right place at the right time to acquire new target consumers.