Comments (2)
It is not surprising that deep and shallow scan show different results. Shallow scan only looks at column names. Deep scan looks at a sample of the data. I've even noticed that two different runs of deep scan show different results as sample rows are different. This is the challenge with not scanning all of the data. Its a trade-off between performance/cost and accuracy. There is no right answer.
W.R.T the output in particular, my observations are:
- Shallow scan should recognize phone, credit card, person and location from column names
- Deep scan did not recognize PII in a few columns. I need to look at the data to figure out if thats a bug or the column did not have any relevant data.
- Deep scan should also scan column names for candidates
- Along with an array, PIICatcher should add confidence numbers.
from piicatcher.
I am closing this issue as I have created specific issues for all the gaps that were identified.
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Related Issues (20)
- ERROR: duplicate key value violates unique constraint "unique_column_name" HOT 1
- shallow scan followed by deep scan causes pk/ uk violations (and possibly viceversa) HOT 3
- Some name columns are identified as phone pii - unable to ascertain why... HOT 2
- Scan snowflake PII catcher HOT 1
- Error parsing info on dropped column during deep (data) detect command
- sqlalchemy.orm.exc.NoResultFound: No row was found for one() HOT 6
- Datahub ingestion function HOT 2
- No row was found for one() when trying Local File
- Support Google Cloud BigQuery HOT 1
- Support Google Cloud Spanner HOT 1
- Unable to Connect to Postgres HOT 5
- Scan can take DAYS on large database clusters HOT 2
- Support OpenMetadata integration HOT 1
- Redshift doesnt support bernoulli tablesample HOT 1
- Unclear example of export to datahub HOT 4
- Unique Constraint Failed HOT 1
- Update ReadMe to accommodate new commands and remove outdated data
- Switches for views, external schemas, remote DBs, etc. HOT 2
- piicatcher installation stuck HOT 6
- Columns names and data are identified incorrectly pii HOT 1
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