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SAMPLE Geospatial Data | Address Validation at Zip Code level | Global coverage | Data cleaning ...

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Databricks2025-02-22 收录
下载链接:
https://marketplace.databricks.com/details/e6c466ca-1ff7-4fa7-8bb0-e0f719651e7f/GeoPostcodes_SAMPLE-Geospatial-Data-Address-Validation-at-Zip-Code-level-Global-coverage-Data-cleaning-
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资源简介:
Our location data powers the most advanced address validation solutions for enterprise backend and frontend systems. A global, standardized, self-hosted location dataset containing all administrative divisions, cities, and zip codes for 247 countries. All geospatial data for address data validation is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom. Use cases for the Address Validation at Zip Code Level Database (Geospatial data) - Address capture and address validation - Address autocomplete - Address verification - Reporting and Business Intelligence (BI) - Master Data Mangement - Logistics and Supply Chain Management - Sales and Marketing Product Features - Dedicated features to deliver best-in-class user experience - Multi-language support including address names in local and foreign languages - Comprehensive city definitions across countries Data export methodology Our location data packages are offered in variable formats, including .csv. All geospatial data for address validation are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Why do companies choose our location databases - Enterprise-grade service - Full control over security, speed, and latency - Reduce integration time and cost by 30% - Weekly updates for the highest quality - Seamlessly integrated into your software Note: Custom address validation packages are available. Please submit a request via the above contact button for more details.
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GeoPostcodes
搜集汇总
数据集介绍
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背景与挑战
背景概述
该数据集是一个全球覆盖的地理空间数据资源,包含247个国家的行政区域、城市和邮政编码信息,专门用于邮政编码级别的地址验证,并每周更新以维持高质量。它适用于地址捕获、验证、自动补全以及商业智能和物流管理等多种场景,支持多语言和多种数据导出格式,便于企业系统集成。
以上内容由遇见数据集搜集并总结生成
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