dbt vs. SAP PowerDesigner

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.

Incentivized

SAP PowerDesigner allows our team of data modelers to work and collaborate from a single repository and single data dictionary. This helps enforce consistency as data elements are referenced in other objects. Prior to our use of PD, we might have an element named "ppt" in one table, "participant" in another table and "part" in a third table. By forcing everything to be used from the data dictionary, we avoid these situations because everyone has to go to the dictionary. And we are able to easily do peer reviews on models before they are released because we are collaborating through the use of the repository.

Incentivized

• 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.

Incentivized

• Impact Analysis
• The domain structure helps you to handle different data types to unify.
• Moving between from conceptual model to logical model and from logical model to physical model is so easy.
• It also excels at implementation of database vendor-specific physical options.
• The repository structure helps you to use in multi developer and architect based organizations by the check in and check out mechanism.
• It also has a fully configurable naming convention implementation.
• Coloring is simple with format copying and pasting option.

Incentivized

• 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)

Incentivized

• It took some time to figure out how to leverage the power of the repository. Some better examples in the documentation would have been helpful.

Incentivized

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.

Incentivized

We did have to reach out to support to learn how to properly utilize the repository feature and share the data model across many developers. Support was able to help us get this set up correctly. The downside was it took us several weeks before we gave up and contacted support. We should have done that earlier. I would say, however, the documentation wasn't clear on how to do this. So support was a great big help!

Incentivized

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.

Incentivized

Oracle SQL Developer Data Modeler : Unfortunately this tool only supports Oracle Databases as a target database, but has many features similar to SAP Sybase PowerDesigner. erwin Data Modeler: Has some issues when switching from Conceptual Model to Physical Model, Impact Analysis, and formatting copy and pasting. Vertabelo: Only supports online models and from a governance perspective, it is impossible for me to connect my target database with an online application because of company policy and regulation requirements.

Incentivized

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

Incentivized

• Standardization of models
• Impact Analysis
• Graphical User Interface
• Ease of deployment

Incentivized