Scroll ignore | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||
K uses a unique algorithm to calculate a data item’s Trust Score.
The Trust Score can help:
Guide data users to utilise trusted data
Help data managers improve the trust level of their data to drive usage
How to locate the Data Trust Score?
Anchor | ||||
---|---|---|---|---|
|
How is the Trust Score Calculated?
Anchor | ||||
---|---|---|---|---|
|
The Trust Score is calculated using a range of attributes including:
The usage of the data product/asset across the Organisation: Frequency and variety of usage
Who uses the data product/asset: Variety and type of users
Use cases: If the data product/asset has been verified for a business use case
Domain: if If the data product/asset has been assigned to a data
Documentation: If the data product/asset has been well documented (e.g. description, owners, and stewards, linked to collections)
Lineage: If the data product/asset provenance is known
Quality of data profile: The number of open Open issues assigned to the data product/asset will penalise its trust score
Each attribute can boost or penalise the trust score. For example:
The more varied and frequent the usage, the higher the trust score
if a data product/asset has been verified, the product/asset’s trust score will be boosted to a high + trust score, even if its usage is only moderate compared to other data products/assets.
If a data product has many issues raised against it, the trust score will be penalised until the issues are resolved.