Footfall Data - 900+ Million Unique Devices - Global Raw Location Data - 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 By filtering these outdated events, we ensure that the data we deliver to our customers is recent and relevant.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.

Quadrant的位置数据集共包含16项属性，涵盖纬度（Latitude）、经度（Longitude）、时间戳（Timestamp）等标准属性，以及Geohash等非标准属性。我们的历史数据可追溯至2019年。我们会对供应商的数据馈送开展严格评估，以保障数据的真实性与品质。我们拥有专属算法，可检测并清理损坏与重复的数据点，使客户能够快速复用我方数据集，仅需开展极少量的数据处理与清洗工作。
Quadrant的移动位置数据会通过去重算法进行处理，该算法以四项核心属性的组合作为判定依据：设备ID（Device ID）、纬度（Latitude）、经度（Longitude）与时间戳（Timestamp）。该算法会遍历全量数据集，识别出这四项属性组合完全一致的数据行；识别完成后仅保留单条副本并剔除重复值，确保客户仅需为完整且唯一的数据集支付费用。
我们会主动在供应链路中识别重复值，以此研判每位供应商的数据价值。我们的数据科学团队开发了一套精密的重复值分析模型，通过基于唯一数据值而非单纯数据体量来评估供应商资质，以此维持高质量的数据馈送——此类举措可为采购方带来显著价值增益。
依托内部数据科学团队，我们可提供专业的技术文档、位置数据算法与查询工具，助力数据采购方快速启动分析工作。
Quadrant的数据噪声算法会自动过滤数据接收前7天内产生的事件，除非客户明确要求获取历史数据。通过筛除这类过时事件，我们可确保交付给客户的数据兼具时效性与相关性。降低延迟同时还能缩减文件体积，实现更高效的数据交付。