dbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.
$0
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SAP LeanIX
Score 8.6 out of 10
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LeanIX in Bonn focuses on controlling and reducing complexity in IT landscapes. Core of the Enterprise Architecture Management solution is an intelligent IT inventory designed to make up-to-date information and planning for the IT landscape accessible for relevant staff. LeanIX also provides an integrable cloud governance solution to its EAM solution via the Cloud Native Tool, as well as the LeanIX Smart Xplore tool to manage Digital Transformation initiatives.
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dbt
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Features
dbt
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Data Transformations
Comparison of Data Transformations features of Product A and Product B
dbt
9.7
8 Ratings
17% above category average
SAP LeanIX
-
Ratings
Simple transformations
10.08 Ratings
00 Ratings
Complex transformations
9.48 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
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.
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.
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.
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!
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.