Product Overview

Data Dictionary

Global Data Counts

About Mobile Location Data



Cross Account Bucket Access



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 (Coming Soon)


All You Need To Know About Data Evaluation

A. Best Practices

B. SDK vs Bidstream Data

C. Data Evaluation using AWS Athena


Location Data Algorithms and Queries

A. Geo-fencing Query

B. Footfall Query

C. Nearest POI Model

D. Location Algorithms



Android Integration

iOS Integration

Integrate with Unity3D for Android

Integrate with Unity3D for iOS


About The Alliance

The Data

Use Cases & Data Science Algorithms

Access APAC Data Alliance Data with AWS S3








The data economy is full of such low-quality data, especially when dealing with location data. Providing the highest-quality location data should be the goal of data providers, and so this is an issue close to home for those of us playing this role in the industry - an issue to be taken seriously. Let’s consider the differences between bidstream and SDK location data:

Bidstream Data


  • Low Quality: Bidstream data is one of the lowest-quality sources of location data, collected from advertising bid requests (info about advertisements like device ID and IP address)
  • Low Accuracy: Accuracy of bidstream data is weak because location data from bidstream can be:
    •   - Derived backwards from the IP address database providers who claim to be able to convert IP addresses to lat/long coordinates, but this is highly unlikely to within any useful accuracy;
    •   - Taken from the cached information stored within the phone’s location settings due to the speed at which ads are required to be requested and placed on apps;
    •   - Entirely fabricated (see the famous case in Kansas)
  • Larger Scale: Due to the large quantities of ad requests across global ad-servers, bidstream location data is readily available in large quantities in comparison to SDK / GPS data
  • Centroids: The problem stems from the fact that when location database providers reverse a devices IP to a lat/long coordinate, people who are connected onto the same IPs will appear on the exact same locations


SDK Data


  • Location SDK: A location SDK collects the user's real-world location from apps on the user's mobile phone.
  • Accuracy: SDKs collect high quality GPS location data with a given indication of the level of accuracy of the signal (known as the horizontal accuracy).
  • Consent: The SDK must obtain user consent through explicit opt-in.
  • Security: The SDK must encrypt and protect user data from app to cloud.
  • Privacy: The SDK must inform about privacy policies and data sharing.
  • Lower Scale: Location SDK data is available in less volume because it requires a direct integration of the SDK into an application, and is, unsurprisingly, more expensive.

Here are some red flags that location data providers can look out for:


  - Lack of movement: This tends to be an indicator of low-quality location data, whereas high-quality data shows lots of movement.

  - “Kansas farm” (and other similar phenomenon): Lots of people at the same coordinate, beyond what’s to be reasonably expected, is always a red flag.

  - Teleportation: By this we mean the same device appearing in multiple countries or regions within the same 24-hour period.


Manual data visualisation helps to spot such instances of low-quality or fraudulent data and remove it before reaching data buyers. In addition to this, our data noise filtering technology plays a key part of our analysis in ensuring high-quality data for data buyers.