five

[SAMPLE] Daily Footfall Data | Local Economic Forecasting Data for Real-estate, Investors, ...|人流量分析数据集|本地经济预测数据集

收藏
Databricks2024-09-24 收录
人流量分析
本地经济预测
下载链接:
https://marketplace.databricks.com/details/7c42eacc-9bb3-4e7a-b5f0-8c4a5ca7b708/Huq-Industries_SAMPLE-Daily-Footfall-Data-Local-Economic-Forecasting-Data-for-Real-estate,-Investors,-
下载链接
链接失效反馈
资源简介:
Overview Huq Industries is delighted to introduce our premium Daily Footfall Data feed, expertly tailored to meet the needs of real estate professionals, investors, retailers, and government bodies focused on local economic forecasting. Our product offers extensive insights into foot traffic patterns across the UK, covering over 2,741 retail centres and utilising more than 1.1 million H3 hexbins at Level 12 resolution. With a robust client base of over 600 satisfied customers, our data is a trusted resource for making informed decisions across various sectors. Key Features and Specifications • Valued by 600+ Customers: Our data is trusted by a diverse client base, proving its reliability and utility across numerous analytical needs. • Accuracy Backtested & Verified: Our data's accuracy is rigorously backtested and verified, demonstrating high correlation with benchmarks such as DCMS / British Museum entrants and sales data from Walmart, Petco, and Boot Barn. • Daily Footfall Statistics: Updated daily to deliver the most current and actionable insights. • UK-Wide Coverage: Comprehensive geographic insights covering the entire United Kingdom. • High-Resolution Data: Hex 12 (19m) resolution ensures detailed and precise geographic information. • Unique Visitor Footfall: Provides clear insights into the number of unique visitors. Why Choose Huq Industries' Footfall Data? > Local Economic Forecasting Our footfall data is an essential tool for local economic forecasting, offering deep insights into foot traffic patterns and consumer behaviour. Real estate professionals, investors, retailers, and government bodies can leverage this data to understand economic trends, predict market movements, and make informed decisions about resource allocation. The granularity and frequency of our data enable precise analysis, which is crucial for accurate economic forecasting. > Foot Traffic Measurement For accurate foot traffic measurement, our data provides detailed insights into visitor numbers, peak times, and movement patterns. This information is invaluable for assessing the performance of retail locations, understanding consumer behaviour, and optimising store layouts and operations. > Asset Management Our data is instrumental in asset management, allowing investors to monitor the performance of their assets accurately. The detailed footfall data helps in evaluating the viability and performance of retail locations, providing a clear picture of asset performance and potential for improvement. > Property Investment Investors can utilise our data for property investment decisions, gaining insights into market demand, foot traffic trends, and consumer behaviour. This information is crucial for identifying high-potential investment opportunities and mitigating risks. > Asset Tracking Our data supports asset tracking, enabling real-time monitoring and assessment of property performance. By understanding foot traffic patterns and consumer behaviour, investors and property managers can make data-driven decisions to enhance asset value and achieve better returns. Data Schema and Cadence Our data schema is designed for clarity and ease of use, featuring properties such as: • Datestamp: The date on which the observation was made. • Polygon ID: The ID of the CDRC defining the enclosing retail centre. • Centre Name: The name of the CDRC retail centre. • Centre Type: The classification of the CDRC retail centre. • Centre Region: The NUTS2/UK2 value for the region where the centre is located. • H3 Key: The H3 ID at level 12 for the geographic unit. • Latitude and Longitude: The geographic coordinates of the H3 unit centroid. • Footfall Value: The number of unique population member observations, adjusted for geographic sampling bias. The cadence of our data ensures daily updates, providing the most current and actionable insights. This regular update cycle allows for timely decision-making and rapid responses to changing conditions, a critical advantage in today's fast-paced business environment. Conclusion Huq Industries' Daily Footfall Data feed is a powerful solution for any organisation looking to leverage location data for strategic advantage. Whether for local economic forecasting, foot traffic measurement, asset management, property investment, or asset tracking, our data provides the quality, frequency, and granularity needed to make informed decisions and drive success. Join over 600 satisfied customers and unlock the full potential of foot traffic data with Huq Industries.
提供机构:
Huq Industries
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4098个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

LFW

人脸数据集;LFW数据集共有13233张人脸图像,每张图像均给出对应的人名,共有5749人,且绝大部分人仅有一张图片。每张图片的尺寸为250X250,绝大部分为彩色图像,但也存在少许黑白人脸图片。 URL: http://vis-www.cs.umass.edu/lfw/index.html#download

AI_Studio 收录

China Groundgroundwater Monitoring Network

该数据集包含中国地下水监测网络的数据,涵盖了全国范围内的地下水位、水质和相关环境参数的监测信息。数据包括但不限于监测站点位置、监测时间、水位深度、水质指标(如pH值、溶解氧、总硬度等)以及环境因素(如气温、降水量等)。

www.ngac.org.cn 收录

MedChain

MedChain是由香港城市大学、香港中文大学、深圳大学、阳明交通大学和台北荣民总医院联合创建的临床决策数据集,包含12,163个临床案例,涵盖19个医学专科和156个子类别。数据集通过五个关键阶段模拟临床工作流程,强调个性化、互动性和顺序性。数据来源于中国医疗网站“iiYi”,经过专业医生验证和去识别化处理,确保数据质量和患者隐私。MedChain旨在评估大型语言模型在真实临床场景中的诊断能力,解决现有基准在个性化医疗、互动咨询和顺序决策方面的不足。

arXiv 收录

Subway Dataset

该数据集包含了全球多个城市的地铁系统数据,包括车站信息、线路图、列车时刻表、乘客流量等。数据集旨在帮助研究人员和开发者分析和模拟城市交通系统,优化地铁运营和乘客体验。

www.kaggle.com 收录

Obstacle-dataset OD

该数据集用于十五种障碍物检测,包含VOC格式和YOLO训练的.txt文件,数据集中的图像来自VOC数据集、COCO数据集、TT100K数据集以及作者团队实地收集的图片。

github 收录