Welcome to the Location Data Blog!

Artificial Intelligence (AI) is rapidly transforming industries, from healthcare to finance, signaling a world where AI isn't just an asset, but a necessity. Yet, the backbone of this transformation —high-quality training data — is facing its own challenges. Contextually rich and representative datasets are vital; without them, even sophisticated AI can perpetuate biases, reducing effectiveness and raising ethical concerns. While broad-spectrum models like GPT-4 absorb varied data, specialized ones crave niche, context-intensive datasets. Unfortunately, many data collection methods miss the mark, leaving gaps in representation.  
 
In our latest solution brief, we dive into these challenges and introduce Quadrant’s Geolancer—a platform designed to revolutionize data collection by offering comprehensive, diverse, and high-quality data.  


 

Earlier this year, we announced that Quadrant had successfully amassed over 1 million Points-of-Interest (POI) using Geolancer, our cutting-edge data collection and verification platform. At the time, our mapping initiatives were gathering a lot of steam as we rapidly scaled our operations to fulfill the soaring demand for accurate and bespoke POI datasets. In line with our projections, this demand has surged even further, prompting us to accelerate our global mapping efforts.  

We are thrilled to share that we have now reached the 2 million POI mark!  

Here, we discuss some recent mapping projects, why Geolancer is so effective for real-world data collection, and how it will evolve to support a wider range of use cases.

Geospatial data – specifically mobile location and Points-of-Interest (POI) data - is a powerful resource that enables everyday location-based services such as ride-hailing, food delivery, logistics, etc. Location data analyses have been proven to optimize commercial operations, identify high-impact public investments, improve our ability to respond to and prepare for natural disasters, and more.   

The location data industry is extremely dynamic because of several reasons, including new policies from dominant OS providers, data-privacy regulations, the ongoing transformation of cities and movement patterns, etc. As it continues to expand and evolve, businesses that  utilize geospatial data (as well as those that supply it) must stay up to date with the ever-changing landscape to maintain a competitive edge.   

Based on our expertise and success with many leading companies across the world, we have authored a report that details the themes and trends we believe will mold the industry in 2023 and beyond. 

Good quality data is crucial for the operational efficiency of location-based businesses. Location-based analyses used in critical decision-making processes rely on the quality and accuracy of data powering them.

However, location data supply chains are characterized by a lack of transparency and authenticity, because data vendors prioritize volume over quality. To ensure that our customers make the most of their data purchase, we have made significant strides in identifying and erasing fraudulent data within our datasets. One way we achieve this is by examining our own data sources and constantly monitoring activity within our mobility and POI data feeds. We use data visualisation and proprietary AI models to spot instances of low-quality or fraudulent data and remove them before reaching customers. 

Quadrant’s POI Data-as-a-Service platform, Geolancer, is superior to conventional POI data collection tools in many ways. Geolancer’s ability to quickly provide high-quality, customizable metadata on demand makes it stand out in a sea of POI data providers. Our bespoke POI datasets allow businesses to increase operational efficiency, build better products, and enhance customer experience.