Open Firmographic Dataset of 323,815 Companies with Addresses, Revenues, and SIC Codes in Amsterdam

An open dataset of 323,815 companies with detailed firmographic information, including addresses, registration numbers, SIC industry codes, revenues, employee counts, and headquarter linkages.
This dataset is designed for researchers, developers, data analysts, and businesses who want to explore company-level economic activity and build data-driven applications.

📊 Dataset Contents

Each record contains multiple fields describing company details. Example fields include:

• Company name & trade name
• Address (street, postal code, city, country)
• Company registration number
• Business category codes & descriptions (SIC codes)
• Yearly revenue (local currency & USD)
• Employee counts (on site & total)
• Headquarter linkages (local, national, global)
• Founding year
• Import/Export codes

🔎 Practical Examples

Here are some example records from the dataset:

1. Luxottica The Netherlands B.V.

   • Registration: 33281895
   • Revenue (USD): $87M
   • Employees: 377
   • Industry: Professional Equipment and Supplies (SIC 5049)

2. ANWB B.V. – Amsterdam Branch

   • Registration: 000018656862
   • Employees: 200
   • Industry: Business Services (SIC 7389)

3. WoodWing Europe B.V.

   • Registration: 34233384
   • Revenue (USD): $1.2M
   • Employees: 6
   • Industry: Computers & Software (SIC 5045)

4. Ouderencentrum Van De Bogt/Westerbeer

   • Revenue (USD): $18M
   • Employees: 94
   • Industry: Medical Offices (SIC 8011)

🌍 Use Cases

• Economic research and market analysis
• Business intelligence dashboards
• Startup ecosystem mapping
• Open data applications and hackathons

🎓 Suggested Research Exercises

Here are some example exercises to practice with this dataset:

1. Industry Distribution Analysis
   Count how many companies exist per SIC code or Business Category.
   Goal: Identify the most common industries and visualize the distribution with a bar chart or treemap.

2. Revenue Insights
   Calculate the total revenue per industry and the average revenue per company.
   Goal: Discover which sectors generate the highest revenues. Extend by comparing subsidiaries vs. independent companies.

3. Company Size Profiling
   Categorize companies into Small, Medium, and Large based on employee count.
   Goal: Understand the structure of the local economy. Cross-analyze with revenue to explore patterns.

4. Headquarter Network Mapping
   Identify companies that are subsidiaries of global groups and map them to their global headquarters.
   Goal: Visualize multinational presence and build a network graph of corporate linkages.

5. Historical Trends
   Analyze founding years to see how many companies were established per decade.
   Goal: Spot patterns in business creation over time and compare across industries.

❓ Questions & Contact

For questions, collaborations, or feedback, please reach out via email:
📧 [email protected]

📥 Source & Licensing

• Source: Collected and curated by Companydata.com (internal data aggregation).
• License: CC BY 4.0
  • You are free to share and adapt the dataset as long as attribution is given.

🔑 SEO Keywords

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