Garbage Data, And What To Do About Them
summary
Defines "garbage data" as data that are not useful for a particular application and gives an operational workflow: ask if the data are relevant to the question, if not test other applications, then determine if data are totally unusable and destroy or label with warning tape. Lists concrete costs — ongoing cloud bills, lost opportunities, staff churn, and bad decisions — and prescribes behaviors: be direct and empathetic, default to treating initiatives as data projects, and be patient while changing practices.
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chapters (4)
- 0:00The problem of garbage data
- 3:37Identifying garbage data
- 8:47The costs of bad data
- 12:20Taking action and best practices
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