QUADRANT DATA OVERVIEW

Product Overview

Data Dictionary

Global Data Counts

About Mobile Location Data

 

RESOURCES

Cross Account Bucket Access

A. AWS S3

Getting Started with Quadrant Mobile Location Data

A. Create a Database, Table and Partition

B. How To Run Basic Location Data Queries

i. Scale and Trend

ii. Depth

iii. Accuracy

C. How Geohash Works 

All You Need To Know About Data Evaluation

A. Best Practices

B. SDK vs Bidstream Data

Location Data Algorithms and Queries

A. Geo-fencing Query

B. Footfall Query

C. Nearest POI Model

D. Location Algorithms

 

SDK INTEGRATIONS

Android Integration

iOS Integration

Integrate with Unity3D for Android

Integrate with Unity3D for iOS

 

ASIA PACIFIC DATA ALLIANCE

About The Alliance

The Data

Use Cases & Data Science Algorithms

Access APAC Data Alliance Data with AWS S3

 
MEDIA LIBRARY

 

FREQUENTLY ASKED QUESTIONS

 

 

 

 

MOBILE SDK LOCATION DATA


What is an SDK?

A software development kit (SDK) is a set of software tools and programs used by developers to create applications for digital platforms – such as iOS, Android, Windows, etc.

If we unpack an SDK, we will find inside resources like libraries, examples of code, processes, and documents. These are tools which helps developers in building their applications.

SDKs also allow app publishers to provide advance functionality. One important example of this would be to provide location data readings from a user’s mobile device. This is achieved by enabling the in-built GPS which most smartphones have.

There are also SDKs that allows app publishers monetisation options. This is commonly done by showing advertisements in the apps, or by collecting anonymous data. The latter is how Quadrant's location data is derived. Note that this is only done when the user’s consent has been granted to the apps they are using.

 

External Factors Affecting the Quality of Mobile SDK Derived Location Data

Now that we understand what mobile SDK and SDK derived location data is, we can turn to the question of how its accuracy, reliability, and density is affected.

Firstly, consumer interactions with mobile device apps impact accuracy. This depends on factors such as whether location services are turned on or off, the duration of time a location-enabled app is open, and whether the user has granted permissions for background location tracking.

The second, are the environmental conditions that impact mobile location data accuracy. This includes factors like how many buildings or trees are around, or how clear the skies are.

Thirdly, hardware technology also impacts the accuracy and reliability of mobile location data. Newer smartphone models are likely to have more accurate readings compared to older smartphone models. 

 

Internal Factors Affecting the Quality of Mobile SDK Derived Location Data

App publishers are to a certain extent able to control the accuracy and density of the mobile location data by:

A. Coding specific instructions on how frequently to log location events from their users.
B. Only log location events within a certain range of horizontal accuracy.

 

For case 1, app publishers can tell their apps to log location events at a certain interval - hourly, every 15 minutes, or even as low as every few seconds.

However, the more frequent the interval, the faster the battery drain is on a users device. This is not desirable for app publishers as battery drain might annoy users and cause them to uninstall the app. App publishers are constantly trying to balance the frequency of data logging and user experience.

For case 2, app publishers can tell their apps to only log location events within a certain range of horizontal accuracy.

Horizontal accuracy is an attribute that shows the uncertainty of the true location of the device. It is expressed as a radius and implies that the true location of the device is somewhere within the circle formed from the radius. The larger the horizontal accuracy of a logged location event, the more uncertainty there is about the true location of that device.

When using the horizontal accuracy filtering method, app publishers are balancing the trade-off between the overall accuracy of the location data collected and the number of events logged. 

We hope you find the information on this page insightful and have a better understanding of Quadrant's SDK derived location data feed.

Quadrant provides mobile location data that can be filtered based on your criteria. Allowing you to receive only high quality location data.