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.

Performing Extrapolation on Location Data to Derive Relevant Insights

Location data is collected from multiple sources of varying quality GPS signals from mobile devices, beacons, and WIFI connections, the notorious Bidstream, and more. In most cases, even genuine location data cannot represent the entire population of the region. This discrepancy can be attributed to smartphone penetration in the country, app-specific demographic variations, hardware inconsistencies, and sources of location data.

To perform meaningful analysis that accounts for mobility patterns and other trends in a larger region, data scientists use projection models to make an accurate estimation of a region’s population and normalise data counts to fit the use case. This is called data extrapolation.

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Geospatial Market Map for APAC - 2021

The intricate web of connected devices and applications produces a lot of location data. Used in the right manner, accurate and timely geospatial intelligence can be leveraged to boost operational efficiency,  improve government and public services, increase marketing and advertising ROI, and expand services to underserved areas.

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Common Problems With Location Data and How to Fix Them

Geospatial data have the potential to uncover valuable insights about the physical world. It can be used by governments to save lives and influence public welfare. Businesses can use it to drive consumer acquisition by capturing the attention of the right people at the right time. Anonymized location data has a lot of value to offer without breaching people’s privacy.

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Methods of Data Delivery for Mobile Location Data

One factor to consider while evaluating location data for purchase is data delivery. Storage costs for big data sets can be substantial, so it is important to get the delivery right. The method of data delivery should take your unique use case into account, as well as the platforms you use to work with the data.

Before making a purchase decision, you should ask your vendor if they are flexible enough to use a delivery method that is in line with your requirements.

In this post, we will discuss the various methods of data delivery and how Quadrant delivers data.

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Buying POI Data: Best Practices for Vendor Selection

High-quality Point-of-Interest (POI) data is the backbone of all location-based businesses and applications. Your customers rely on you to find day-to-day services such as transportation, food delivery, online shopping, and more. The speed, accuracy, and reliability in providing these services can be a determining factor in gaining and retaining customers.

But how do you ensure that the data powering your business are of good quality and up to date?

There are numerous data providers that claim to offer vast, accurate, and ideal POI datasets, but how do you correctly assess them? In this post, we will discuss a few factors to consider before buying POI data. Use them as a checklist for your purchase decision while selecting a data vendor!

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