Aggregated Foot Traffic Data - Global Raw Location Data - 900+ Million Unique Devices - Quadrant

Quadrant's location data contains 16 attributes, including standard attributes such as Latitude, Longitude, and Timestamp, and non-standard attributes such as Geohash. Our historical data spans as far back as 2019. We conduct stringent evaluations on supplier feeds to ensure authenticity and quality. Our proprietary algorithms detect and cleanse corrupted and duplicated data points - allowing you to leverage our datasets rapidly with minimal data processing or cleaning. Quadrant’s mobile location data is processed through a deduplicating algorithm that focuses on a combination of four important attributes: Device ID, Latitude, Longitude, and Timestamp. This algorithm scours our data and identifies rows that contain the same combination of these four attributes. Post-identification, it retains a single copy and eliminates duplicate values to ensure our customers only pay for complete and unique datasets. We actively identify overlapping values at the supply level to determine the value each supplier offers. Our data science team has developed a sophisticated overlap analysis model that helps us maintain a high-quality data feed by qualifying suppliers based on unique data values rather than volumes alone – measures that provide significant benefits to our buyers. Through our in-house data science team, we offer sophisticated technical documentation, location data algorithms, and queries that help data buyers get a headstart on their analyses. Quadrant’s Data Noise Algorithm weeds out events that occurred seven days before the data is received (unless historical data is requested). By filtering these outdated events, we ensure that the data we deliver to our customers is recent and relevant. Reducing latency also decreases file sizes, which results in more efficient data delivery.

搜集汇总

背景与挑战

背景概述

该数据集提供全球范围的聚合人流位置数据，覆盖超过9亿台独立设备，历史数据可追溯至2019年，并包含经纬度、时间戳和地理哈希等属性。通过严格的供应商评估、专有去重和去噪算法确保数据质量，同时提供技术文档支持，帮助用户高效启动分析。