Data at Work

The world of data and its many applications. This blog will help you learn how visionary companies are utilising external data to enhance business operations.

Geolancer and the role of big data in Augmented and Virtual Reality

For several millennia, human beings have delved into alternative realities to entertain themselves and cope with the pressures of everyday life.Until recently, the mediums that enabled these experiences included fictional storytelling, music, art, movies, and TV shows. However, due to the exponential increase in computing power, the last decade has witnessed the rise of the most immersive forms of such mediums to date: Augmented Reality (AR) and Virtual Reality (VR). This blog post sheds light on this growing industry and discuss how Quadrant’s POI datasets can enrich AR and VR platforms – now and in the future.  

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Using AI to clean Personally Identifiable Information from user-generated data sets

Having access to large repositories of data enables businesses to optimise operations in several ways. This includes personalised advertising, greater supply chain efficiency, and more satisfying customer experiences.

However, people have grown increasingly wary of trusting businesses and governments with their data. Several high-profile data privacy breaches at LinkedIn, Alibaba, and Yahoo (to name a few) collectively impacted billions of users.

Ethically managing data and making sure no Personally Identifiable Information (PII) makes it to big data sets is a challenge we take very seriously at Quadrant.

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How to use location data in transportation and mobility

Transportation companies need location-based intelligence to gauge demand, support operations, adapt to changing public requirements, and ensure safety. Reliable and accurate mobile location data is key to studying mobility trends that can reveal actionable insights for the betterment of infrastructure and applications in supply chain, ride sharing, public transport, traffic management, and other use cases.

Companies also need location data to assess potential for usage in growing urban spaces to improve availability and return-on-investment. More recently, due to the Covid-19 pandemic, people’s movement patterns have changed drastically. The new normal with social distancing requires tweaking existing forms of transportation and related services. All these make mobile location datasets and corresponding mobility analysis more valuable than ever, both in the private and public sector.

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Reducing Data Preparation Costs & Increasing ROI with Mobile Location Overlap Analysis

The location data industry is using multiple sources of data with a varying degree of quality. This means suppliers often have a significant amount of overlapping records. While this does not impact quality or validity of the data, it poses a challenge for buyers who need unique values for their analyses.

Most off-the-shelf vendors leave this unaddressed as it makes their data volumes appear larger. However, when buyers prepare the data for analysis by removing overlaps, they often see a significant drop in overall volumes. 

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User behaviour and POI data quality in Geolancer – Quadrant quarterly hackathon

Earlier this year, we launched the public beta test of our proprietary POI collection and verification app, Geolancer. Aimed at providing up-to-date and manually-verified POI datasets, Geolancer is already helping ride sharing and real estate companies enrich their platforms with a hyper-accurate POI data feed. In this article, we provide a peek behind the curtain and explain how we maintain the high quality of POI data in Geolancer.

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