Metadata
- Author: Dan Poppy
- Full Title:: Ep 47: Ramp’s $8 Billion Data Strategy
- Category:: 🗞️Articles
- Document Tags:: Data Culture, Data Culture,
- URL:: https://roundup.getdbt.com/p/ep-47-ramps-8-billion-data-strategy
- Finished date:: 2023-08-12
Highlights
I’ve learned is that business logic always finds a way to be written. We have really smart and technical and resourceful and fast-moving stakeholders, and what we found is that core reporting ended up in other systems, and oftentimes, it was unexpected. We have a lot of business logic at the edge. (View Highlight)
Omg, this is crazy
There’s definitely been hiccups along the way, but I think overall it’s led to healthier code. People are excited to write dbt, especially people that are not necessarily on our team. We have a lot more centralized business logic as well as visibility into usage. As a result, we’re moving a lot faster (View Highlight)
The big thing I learned is always ask your stakeholders what they actually look at to make decisions. You might think and hope it is the gorgeous Looker dashboard built on beautifully normalized Kimball model dbt but oftentimes it’s not. You’ll often be surprised. It’s on us as data leaders to look at what people are actually using to make decisions (View Highlight)
moving data from Google ads to Snowflake (View Highlight)
This clearly suits the narrative of dbt
For us, that’s not strategic. We can take a dependency on Fivetran, and I’m confident Fivetran is going to be better at that next year than this year. (View Highlight)
Knowing if a company has lost a lot of money in their bank account is really important. So, in some instances, I would say these things graduate up from dbt Snowflake to dbt Materialize and are still the purview of the data team. In other situations, we say, “Look, this is no longer a reporting metric, this is a state of a business and it is a production grade input to all of our systems.” We actually want to adopt and rewrite this in our core transactional databases. In terms of organization, we have seen some stuff not only graduate out of Snowflake and dbt, but out of the hands of the data team entirely. We view this as a massive success. (View Highlight)