Global 2000 Companies (2025)

**AI-ready dataset for business partner analytics and visualization**

This dataset provides standardized, enriched information on 2,000 of the largest global companies, based on publicly available data. It is designed to support both analytical workflows and AI applications, thanks to its comprehensive scope and semantically well-documented data fields.

Included are granular business partner attributes such as:

- Legal and international names
- Legal form and identifiers (e.g., EIN, LEI)
- Registered and headquarter addresses with geographic coordinates
- Standardized industry classifications (NACE, NAICS, SIC)
- Key financials for 2024 (Revenue, Profit, Assets, Market Capitalization)
- Narrative company profiles

The data is structured according to the [CDQ Business Partner Data Model](https://cdq.pro.wiki/Public:CDQ_data_model), which ensures semantic consistency and traceability across jurisdictions.

This dataset demonstrates the power of structured, high-quality data in enabling business partner insights, AI-based enrichment, and compliance use cases.

Created and shared by [CDQ](https://www.cdq.com), a leading provider of trusted business partner data with a global knowledge base of over 200 million company records.

原始信息汇总

Global 2000 Companies (2025) 数据集概述

数据集基本信息

• 数据集名称: Global 2000 Companies (2025)
• 提供商: CDQ AG
• 访问权限: Free (Unlimited Access)
• 数据刷新频率: Static Data
• 地理覆盖范围: Global (By latitude and longitude)
• 云区域可用性:
  • AWS (Africa (Cape Town), Asia Pacific (Jakarta), Asia Pacific (Mumbai), Asia Pacific (Osaka) 等45个地区)

数据集描述

• 提供全球2000家最大上市公司的标准化、丰富信息。
• 数据支持分析工作流和AI应用，包含全面的业务合作伙伴属性和语义化文档字段。
• 主要属性包括：
  • 法律和国际名称
  • 法律形式和标识符（如EIN、LEI）
  • 注册地址和总部地址（含地理坐标）
  • 标准化行业分类（NACE、NAICS、SIC）
  • 2024年关键财务数据（收入、利润、资产、市值）
  • 公司简介

业务需求

• 数据质量与清洗: 提供统一和丰富的公司主数据，支持替换分散、不完整或不一致的数据。
• 市场分析: 支持全球市场动态、行业趋势和竞争对手分析。
• 客户入职: 加速入职流程，减少手动验证。
• 位置数据丰富: 提供完整地址层次结构和地理坐标。
• 位置地理编码: 支持空间分析和基于位置的洞察。
• ESG投资分析: 支持ESG评分和筛选。

数据字典

• 表名: COMPANIES
• 内容: 包含公司记录，包括本地和国际名称、法律和总部地址、行业分类、财务数据和业务摘要。
• 特点: 每个属性都包含语义元数据（URLs、技术键），支持自动集成和统一。

使用示例

1. 查询全球2000家公司的总部位置和名称: sql SELECT data:names[0].value::STRING AS name_legal, data:names[1].value::STRING AS name_international, addr.value:country.shortName::STRING AS country_hq, addr.value:geographicCoordinates.latitude::FLOAT AS latitude_hq, addr.value:geographicCoordinates.longitude::FLOAT AS longitude_hq FROM companies, LATERAL FLATTEN(input => data:addresses) AS addr WHERE addr.value:types[0].technicalKey = HEADQUARTER;

2. 按收入排序的全球顶级公司及其总部位置: sql WITH names AS ( SELECT c.data:addresses AS addresses, f.value:type.technicalKey::STRING AS name_type, f.value:value::STRING AS name_value, c.data:profile.financials AS financials FROM companies c, LATERAL FLATTEN(input => c.data:names) AS f ), names_pivoted AS ( SELECT addresses, financials, MAX(CASE WHEN name_type = INTERNATIONAL THEN name_value END) AS name_international, MAX(CASE WHEN name_type = LEGAL THEN name_value END) AS name_legal FROM names GROUP BY addresses, financials ), hq AS ( SELECT COALESCE(name_international, name_legal) AS name, addr.value:country.shortName::STRING AS country, addr.value:geographicCoordinates.latitude::FLOAT AS latitude,

3. 按法律地址国家统计公司数量: sql SELECT addr.value:country.shortName::STRING AS country, COUNT(DISTINCT c.data:names[0].value::STRING) AS company_count FROM companies c, LATERAL FLATTEN(input => c.data:addresses) AS addr WHERE addr.value:types[0].technicalKey = LEGAL GROUP BY country ORDER BY company_count DESC;

分类

• AI & ML
• Customer Onboarding
• Data Engineering
• Data Quality and Cleansing
• ESG Investment Analysis
• Geospatial
• Location Data Enrichment
• Location Geocoding
• Market Analysis

联系方式

• 销售: [e-mail]
• 支持: [e-mail]

法律条款

• 条款类型: Standard

关于CDQ AG

• CDQ专注于帮助企业管理主数据，确保数据准确、可靠和实时。拥有18年的数据质量和数据共享经验，结合智能自动化和协作采购，提供高质量数据解决方案。

搜集汇总

背景与挑战

背景概述

该数据集收录了2000家全球最大企业的标准化信息，包含法律名称、地址、行业分类、2024年财务数据等详细属性，采用CDQ商业伙伴数据模型确保数据一致性，适用于商业分析和AI应用。数据由专业机构CDQ提供，源自其覆盖2亿企业记录的全球知识库。