Composable DataOps Platform vs. dbt

They need to better identify what their product excels at. I'm continually trying to think of new ideas to run through Composable Analytics. They need to better Identify what this product shines at and market themselves to that subset of an industry

If you can load your data first into your warehouse, dbt is excellent. It does the T(ransformation) part of ELT brilliantly but does not do the E(xtract) or L(oad) part. If you know SQL or your development team knows SQL, it's a framework and extension around that. So, it's easy to learn and easy to hire people with that technical skill (as opposed to specific Informatica, SnapLogic, etc. experience). dbt uses plain text files and integrates with GitHub. You can easily see the changes made between versions. In GUI-based UIs it was always hard to tell what someone had changed. Each "model" is essentially a "SELECT" statement. You never need to do a "CREATE TABLE" or "CREATE VIEW" - it's all done for you, leaving you to work on the business logic. Instead of saying "FROM specific_db.schema.table" you indicate "FROM ref('my_other_model')". It creates an internal dependency diagram you can view in a DAG. When you deploy, the dependencies work like magic in your various environments. They also have great documentation, an active slack community, training, and support. I like the enhancements they have been making and I believe they are headed in a good direction.

Incentivized

• Flexible Dataflow Application
• Easy to source data and then compose to create actionable items for supporting decision
• Allowed to do different analysis
• Extremely powerful tool to digest information to produce insight from the data

• user experience makes it easy to work with SQL and version control
• customer success team and the dbt (data build tool) community help establish best practices
• thorough and clear documentation

• I can not really comment because I do not have a complete fluency with the product as of now.
• Recreating the wheel on some uses but i guess that may be user error.

• Slow load times of the dbt cloud environment (they're working on it via a new UI though)
• More out-of-the-box solutions for managing procedures, functions, etc would be nice to have, but honestly, it's pretty easy to figure out how to adapt dbt macros

Incentivized

This is an extremely productive tool.

I would compare them to custom system like Morgan Stanley has that I use. A more appropriate company is Novus or LightKeeper. This product is potentially much cheaper but Novus and Lightkeeper already have built in Analytics screens that you could potential build yourself with Composable.

Most ETL pipeline products have a T layer, but dbt just does it better. The transformation is on steroids compared to the others. Also, just allows much more Adhoc solutions for very specific projects. Those ETL tools are probably better on the T part if you don't need too many transforms - also dbt is pretty much free dependent on how you work it, also extremely scalable.

Incentivized

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

Incentivized