In order to be classified as a 'Product,' a dataset must adhere to strict foundational criteria. These six characteristics guarantee that data is valued as a top-tier asset, producing seamless benefits.
For a Data Product to be considered authentic, it must demonstrate these six fundamental attributes in order to reduce customer resistance and enhance credibility.
Users should not need to depend on tribal knowledge when accessing data. Data products should be easily searchable within a centralized or federated data catalog.
Also referred to as Addressable, the data product must offer a distinct, programmatic address for secure access to the information once it is located.
To rely on the data without conducting personal validation checks, consumers need assurance of SLAs and clear lineage.
A product should be intuitive enough that no engineer is needed to explain it; schemas, semantics, and syntax should be integrated seamlessly with the data.
Standardization across the enterprise enables seamless integration of data from different domains.
Security should not be an afterthought; access control, masking, and encryption must be managed locally and overseen globally.
Lacking these essential qualities, a 'Data Product' is merely a table thrown into a data lake. The aim of these six pillars is to eradicate any obstacles for consumers.
A Data Scientist or Analyst can quickly generate insights in hours instead of weeks when they come across a dataset that is self-describing, guaranteed to be accurate through SLAs, and accessible via standard SQL.
Shifting the focus from data movement to data usability and value, Data as a Product ensures that data is valuable and usable upon arrival.
Utilize our assessment tool to evaluate your current datasets based on the six fundamental DaaP attributes and pinpoint any deficiencies in your system design.