Unlock Location Intelligence Capabilities with CARTO’s New Data Enhancements

Unlock Location Intelligence Capabilities with CARTO's New Data Enhancements

The Announcement Includes Integration of Third-Party Data Streams, a New Interface for Data Scientists Designed to Augment Location Intelligence Analytics

Madrid-based location intelligence platform, CARTO, has unveiled a new data strategy at the ongoing CARTO Locations conference. The new data strategy is anchored on derivative data streams, which optimize modern location data sources to help organizations to better harness the power of location intelligence across a variety of business challenges.

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CARTO Location Intelligence
CARTO Location Intelligence

CARTO Brings Newly Available Data Streams to Solve Business Problems

Javier de la Torre
Javier de la Torre

At the time of this announcement, CARTO CEO Javier de la Torre, said, “Organizations want to benefit from the modern data sources made available by IoT and Big Data, but we often hear from them that they are limited to the information they collect, or too outdated, point-in-time data sets.”

Javier added, “We are taking the lead to make it easy for these organizations to actually use those newly available data streams to solve business problems.”

Read More: How is The Location Data Landscape Shaping Up in 2018?

CARTO Platform Adds More Muscle with Raw Data Streaming

Derivative data streams, which pull raw data from actual business transactions and events, as opposed to traditional, static demographic data to create brand new data sets not available anywhere else, will be included in CARTO platform for the first time. These streams are combined from multiple sources such as financial transactions, GPS and telco, social media, vehicle sensors, and more to allow citizens, governments, and organizations to make decisions based on the current state of a situation rather than making assumptions on what likely happened in the past.

Available immediately, the Foot Traffic data layer combines mobile events and GPS data to measure the number of pedestrians in transit to and from distinct locations.

Users can leverage insights about foot traffic to make critical business decisions such as site selection, marketing planning, competitive analysis or sales forecasting. This is available through CARTO’s Data Observatory, which already includes a wide variety of datasets from a network of industry-leading partners such as Zillow, the Consumer Data Research Centre, and the National Institute of Statistics and Economic Studies.

How CARTO’s Data Science Team Cleans and Removes Biases in the Data

Typically, raw data collected is difficult to work with and contains biases which often lead to errors in decision-making. In addition to anonymizing and aggregating the data to ensure responsible use, CARTO’s Data science team cleans and removes biases in the data, making it ready for spatial analysis and visualization. Organizations can immediately combine it with their own data and Location Intelligence solutions for more comprehensive analyses.

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To make these new data sources more accessible for analytics, CARTO is also announcing the ability to query data from its Data Observatory through CARTOframes, meaning data scientists can leverage CARTO data through Python programming language without leaving their Python environment. CARTOFrames creates connectors to the CARTO Data Observatory so data scientists can supplement their own data with third-party sources for better models, predictions, and machine learning processes in their preferred environment.

Powerful Location Intelligence Platform Can Turn Location Data into Better Behavioral Marketing Asset

Currently, CARTO is at the pinnacle of the location intelligence revolution. The Location Intelligence platform turns location data into better behavioral marketing, optimized delivery routes, strategic store placement, and maximized assets. Everyone, from data scientists to business analysts, use our open, cloud software to understand where things happen, why they happen and predict what will happen in the future.

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