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Data Quality & Observability

Created Nov 18, 2023

20 members

218 discussions

The Data Quality & Observability section of the Collibra Community is focused on ensuring trust in data through quality monitoring and observability practices. It’s where users explore tools, workflows, and strategies to assess, track, and improve the health and reliability of their data assets across the enterprise.

Asset Import & Export
8 members
16 discussions

hyoosaf
9 days ago
Postgres metastore tables where the metabar details of Collibra DQ dataset findings page are stored

Hello there, Can anyone help me understand from which Postgres metastore tables the metabar details of Collibra DQ dataset findings page are fetched - Screenshot attached. To be more specific, would like to know where the below are stored : 1.column count 2.Source details 3.Data Category Thanks, Hazeena
4
Dan_Everett
1 month ago
Understanding Rule Scores
There is some new documentation to help you better understand rule scores. https://productresources.collibra.com/docs/collibra/latest/Content/DataQuality/DQCoreComponents/Rules/co_rules-score.htm

3
saritawaghmare
3 months ago
Rule migration from DQ to DG(DQ to DG rule integration)
HI Team, I need to know rule created in DQ i.e. migration from DQ to DG. Kindly guide or provide link if any video or documentation related to this. Thanking you. Regards, Sarita

2
user_c96dfe
3 months ago
Best practices for integration of CDQ results in DIP
By default, CDQ creates three domains per tenant and/or dataset in DIP when activating an integration. Are there any best practices how to structure the assets in DIP?

1
Community_Alex
4 months ago
The Education team is proud to announce a new Data Quality Steward Certification available to our customers and partners!
The Education team is proud to announce a new Data Quality Steward Certification available to our customers and partners! Administered through our new testing platform, Certiverse, this exam features enhancements such as ID verification, exam proctoring, and automatic badging for those who pass. Want more information about the role and what the exam covers? Check out the factsheet . Want to prepare for the certification exam? Take our new DQ Steward learning path . Ready to enroll in the exam? Visit the Certifications page on university.collibra.com . The cost of the exam is $125 (paid via credit card): Premium Education subscribers are given two free exam attempts Take the exam before the end of the year and get 50% off using the promo code EOYDQS

2
user_56c19d
5 months ago
apply custom dq rule to more than one dataset
If I create a custom simple rule on a dataset is there a way to apply that same rule to another dataset? For example I want to apply a completeness check on a column in one dataset that is based on a subset of data on an individual table and then I create another dataset against that same table for a different subset of data and the same column needs a completeness check, is there an easy way to copy it over without recreating the whole rule?

3
hyoosaf
6 months ago
Behavior rules - Upper bound and lower bound calculatuion
Hello Collibra friends, Can somebody share how the behavior check, row-count generates the lower bound and upper bound adaptively and predict a range after the learning phase..

1
hyoosaf
7 months ago
DQ job score 100 when run with zero data in the source
We have a scenario where we would like to show 0 score when there is no or ZERO records in the source table and an alert message sent on this. We could create the alert using stat rule check rc=0, but the job shows 100 as the score with zero records in the table. Tried the same stat check $rowcount=0 as a custom rule and give it 100 absolute points when broken, but the custom rules seem to run only when there is any data in the table. The adaptive check on $rowcount should be kept to learn by itself to adapt to the rowcount variences. Is there any other option of setting the overall job score to 0(ZERO) when there is no data in the source table?

0
kritikachhabra
7 months ago
Migrate DQ job from collibra DQ dev to Collibra DQ prod
Hi, Is there a migration mechanism in collibra DQ to migrate the DQ jobs and rules from dev to prod in collibra DQ application? Thanks in advance

3
kaiting_koh
9 months ago
Collibra DQ unable to join dataset using @
For a specific dataset created, Collibra is not able to see it as a dataset name and is throwing error - Exception with freeform sql rule check: extraneous input '@' expecting ... Usually if @dataset is registered, the query will change the name of the dataset from @dataset to <dataset>_dataset in the Rules preview. The following conditions were met - name of first dataset matches name of main dataset which rule is created joining dataset has a quality >75% May I know what other configuration has to be done? Note once I change it from Freeform SQL to Native, it works. Something is wrong with the freeform SQL? However, I need to store the rule breaks in metastore hene native SQL is not an option even though rule is working fine there.

0

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