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TO BE REVIEWED: What type of AI techniques (eg. Random Forest) does Collibra DQ Use?
Q: What type of AI techniques (eg. Random Forest) does Collibra DQ Use? Answer: It is important to realize that we have many aspects to Collibra DQ and they don’t all use the same algorithms. Does that make any sense? I will give you some examples: Outlier detection: We use Interquartile Range (“I
Questions
TO BE REVIEWED: DQ Agent configuration with multiple Apache Spark -conf key value pairs
Q: How do I configure the DQ Agent with multiple Apache Spark -conf key value pairs. I tried using more than one -conf in the “Free Form (Appended)” text field in the “Edit Agent” configuration dialogue, but that only accepts the first -conf some.key=value and ignores the second. Answer: Milind Pan
Questions
job.catalog.JdbcIngestionJob error on databricks JDBC
Hello, all I tried to connect Azure Databricks using Collibra JDBC Driver. I’ve set up the connection via the Catalog successfully with the Driver downloaded from https://marketplace.collibra.com/listings/jdbc-driver-for-databricks/ But I got an error. I guess it might because of the single quote
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Integrations
TO BE REVIEWED: How do I use that Collibra DQ "Deployment Mode" Dialogue to override the default Agent configuration?
Question: I want to manually override the default Agent settings when running my Collibra DQ job. How do I work with the Deployment Mode dialogue? A: We created this presentation to get you started with using Apache Spark in DQ: https://docs.google.com/presentation/d/1epc_0xgpaaIsatEy15BCbhyEsRjMlK9
Questions
Closed
TO BE REVIEWED: How can I access my Databricks cluster using Collibra DQ?
Q: How can I access my Databricks Delta Lake cluster via JDBC? Answer from Brian Mearns: Based on the recurring feedback, we decided to prioritize the development. The expected release date is 2022.05 for a default-packaged Databricks JDBC connector. There are 3 primary ways customers desire to use
Questions
TO BE REVIEWED: How can I configure Collibra DQ to run a large DQ Check Job (containing millions of rows of data)?
Question: How can I configure Collibra DQ to run a large DQ Check Job (containing millions of rows of data)? Answer: We have some customer reports to us, sharing their configuration of Apache Spark, Kubernetes (K8s), Docker, and more: Collibra DQ ran on K8s Docker: 150 Million rows, with 31 column
Questions
Issue with Snowflake Pushdown
Hi All, I am trying to create a Data Quality Check on Snowflake Tables, My Column Names are like "First Name", "Last Name" , "High School" etc ( placeholder), when I try to create a DQ Check , with pushdown enabled, Collibra DQ transform's the column name to First_Name, Last_Name etc, then trying t
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Use cases
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..
Questions
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Data Quality & Observability
REVIEWED-FINAL: Technical: DQ Connections / Connectors
Top Links Supported DQ Connectors: [Click Here] Connectors / Support Q: Is there a list of all supported DQ connectors? A: https://docs.owl-analytics.com/connecting-to-dbs-in-owl-web/owl-db-connection/supported-drivers A: Please note that some drivers marked as ‘Some Testing’ e.g. MongoDB are in Tec
Questions
Apache Spark in Collibra DQ with Py4J (need Spark v. 3.01, and correct Scala version)
Python and Py4J code: owl.owlCheck() fails with an exception: File “/opt/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py”, line 1305, in call File “/opt/spark/python/lib/pyspark.zip/pyspark/sql/utils.py”, line 128, in deco File “/opt/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py”,
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Data Quality & Observability
Rules details export shows difference with respect to summary details
Has anyone experienced a difficulty in interpreting the export of rules details in a data quality job.? The export shows much larger difference with respect to the summary details in a data quality job findings that uses a pushdown connection.
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Data Quality & Observability