dbt vs. Informatica Cloud Data Governance, Access and Privacy

The prerequisite is that you have a supported database/data warehouse and have already found a way to ingest your raw data. Then dbt is very well suited to manage your transformation logic if the people using it are familiar with SQL. If you want to benefit from bringing engineering practices to data, dbt is a great fit. It can bring CI/CD practices, version control, automated testing, documentation generation, etc. It is not so well suited if the people managing the transformation logic do not like to code (in SQL) but prefer graphical user interfaces.

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The Informatics vision is already determined and with the relationships already configured, or that plasters any new type of vision or relationship between the Assets. As a result, a pedigree diagram is poor and limited with the availability of information on the screen or in reports for consultation and decision making. It has an approval and maintenance workflow that is also limited to assets already made available only by Informática. It will not be possible to see the connection of a technical, functional, and documentary line in a single flow. It allows the registration of all data referring to a DPIA and LIA, but it does not generate a report that allows the aggregation of this set of information in a single place. The tool makes information available to support a decision regarding the DPIA and LIA, but it does not make it available in a unified way as in a report.

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• dbt supports version control through GIT, this allows teams to collaborate and track the data transformation logic.
• dbt allows us to build data models which helps to break complex transformation logic into simple and smaller logic.
• dbt is completely based on SQL which allows data analyst and data engineers to build the transformation logic.
• dbt can be easily integrated with snowflake.

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• automated sensitive field detection
• replace critical data with dummy but real-looking data
• threat detection
• role based access

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• Field-level lineage (currently at table level)
• Documentation inheritance - if a field is documented the downstream field of the same name could inherit the doc info
• Adding python model support (in beta now)

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• High Complexity, requires training.
• As it does not allow customization in relationships such as information separately in visual form and even in other tools of the Informatics group such as EDC.
• Navigation is complex.

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dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.

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I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT there's a FREE version for 1 dev seat with no read-only access for anyone else, so you can always start with that and then buy yourself a seat later.

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Overall experience with Axon is average and it is a very manual product. Axon is a very good tool for data governance. User-friendly interface and is integrated with multiple systems.

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• Simplified our BI layer for faster load times
• Increased the quality of data reaching our end users
• Makes complex transformations manageable

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• risk mitigation
• data loss prevention
• role based data access

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info