This document discusses location intelligence and geospatial databases. It provides examples of how analyzing location data can help predict walking paths, populations affected by transportation changes, poverty levels, and business opportunities for ridesharing companies. The document promotes CARTO as an open and powerful platform for discovering insights from location data and lists industries that generate large amounts of location data like telecom, banks, utilities, and health. It envisions high performance analytics on geospatial databases and notes CARTO is hiring.

1. Database Driven
Location Intelligence:
The Missing Dimension
Javier de la TorreFounder & CEO, CARTO
PREDICT THROUGH LOCATION

2. PREDICT THROUGH LOCATIONGEOSPATIAL DATABASE ON THE CLOUD
As of last thursday...
CARTO is an open, powerful, and intuitive
platform for discovering and predicting the key
insights underlying the location data in our
world.

3. (Michael

5. most likely walking paths of 114,000 people walking to the L train
Sources:
Census data - ACS
Commuting - LODES
Routing - OSM

6. Affected populations by the closing of the L train

7. Clustering block data to determine poverty status

8. Uber & Lyft are going to have a great ride in Williamsburg and Greenpoint

9. What are the alternatives?
Considering the shuttle would take 20min?
Take a bus shuttle
Use the M line
Use the A line

10. If the bus shuttle takes more than 20min people will use other routes
But 75,000 riders could still need shuttles
If shuttle takes more than 28min. we might need another bridge
53,000 riders will still need to take them. That is 816 buses per day
or a full bus every minute and a half.

11. WHERE to inform citizens
WHERE to add extra service
WHERE Uber can do marketing
WHERE companies will be most affected
WHERE
WHERE
WHERE

20. Everything happens somewhere

21. Relating things based on where
they happen
No need for Foreign Keys!

28. AND WHERE ARE WE GOING...
OR MORE SPECIFIC WHERE WE BELIEVE IT NEEDS TO BE GOING

30. Telecoms | Banks | Mobile apps | Utilities | Cars | IoT | Earth Observation | Health
Major industries generating huge
streams of location data
Telemetry
Credit card transactions
Logs
Measurements
GPS Logs
LiDAR
Feature changes
….

31. GeoJINNI GeoTrellis
Open Source is moving...

32. HIGH
PERFORMANCE
ANALYTICS
PostGIS built on Spark
ETHNIC DIVERSITY OF THE US SHOWING ONE POINT FOR
EVERY 100 PEOPLE OF A GIVEN ETHNICITY

33. Javier de la Torre
@jatorre
Founder & CEO, CARTO
PREDICT THROUGH LOCATION
Thanks!
We are hiring!