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Synthetic data for the The Netherlands Chamber of Commerce (KVK)

Details
Organization

Organization

Dutch Governmental Organization

Location

Location

The Netherlands

Industry

Industry

Governmental

Size

Size

1,500+ employees

Use case

Use case

Analytics, Test Data

Target data

Target data

Business register data

About the client

The Governmental organization serves as a central resource for business-related information in the Netherlands. It maintains a business-related database. The organization aims to enhance its relevance for organizations by facilitating relevant support services to accelerate (starting) organizations in building, maintaining, and improving their competitive position.

The situation

Data plays a vital role in this ambition by facilitating organizations with relevant support services, market research, and insights. As for leveraging this data potential, the organization organized a 2-day hackathon for internal colleagues to spot and build new initiatives. As a foundation for this hackathon, internal data sources would be valuable to utilize to open new data-driven initiatives. However, privacy protection is crucial, and the organization must balance the accessibility of business information with safeguarding sensitive data and complying with relevant privacy regulations.

The solution

Hence, a synthetic version of the organization data is used in the context of this internal hackathon to spot and build data-driven solutions during this fast-paced 2 days hackathon. Synthetic data was generated to mimic real business register data while ensuring privacy and data protection. This synthetic dataset can enable participants in the hackathon to develop and test innovative solutions, algorithms, and applications without using actual sensitive business information. In addition, synthetic data is used as test data in the development, test, and acceptance environments.

The benefits

Privacy-by-design hackathon with representative and actionable data

Data plays a significant role in this hackathon. Data preparation for public hackathons requires a lot of time and effort. Additionally, data anonymization makes data less accurate and more abstractive, which influences the data science models’ performance. Synthetic data is used to allow every participant to work with relevant and representative data, without exposing actual individuals.

Innovative hackathon initiatives on relevant data

Various new data initiatives were introduced by the organization’s colleagues during this hackathon to enhance its relevance. These initiatives will be taken forward as a starting point for implementing its data-driven strategy to accelerate organizations in building, maintaining, and improving their competitive position.

Fast access to data

Data access requests for the relevant data used during the hackathon would otherwise take months. Hence, this hackathon allowed for fast access to relevant data to utilize the full momentum of building new data initiatives.

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