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The popularity score for data products on DataHub is calculated by two key metrics: product views and purchases. We analyze the clicks each data product receives, offering insights into user interest.
Simultaneously, we track the conversion of this interest into transactions by monitoring the number of purchases for each data product. Our calculation then provides a balanced assessment, enabling users to identify products that are best relevant to their searches, based on both significant views and consistent conversions.
Our commitment to user engagement is handled anonymously, designed to enhance your platform experience while respecting your privacy.
Ensuring the quality of our data products is a multifaceted process, considering various dimensions to provide users with relevant insights. We evaluate the quality of documentation associated with each data product, emphasizing the need for clear, detailed information.
Usability metrics play a crucial role, assessing factors such as how easily users can navigate and utilize the data product, taking into account its coverage, compatibility with different cloud providers, and availability in various regions.
The calculation of the quality score involves a normalization formula that standardizes these diverse metrics, offering a unified measure of a data product's overall quality. The UnionAll formula serves as the mechanism to aggregate these metrics, providing users with a holistic understanding of the quality of each data product available on our marketplace.
