You are convinced that you need DataOps..

You are concerned about the long lead times of your data projects and burnout of your data team in chasing the business needs. You are convinced that DataOps is going to be a huge step to alleviate the pain.

If you don't know what DataOps is or why you need it, this post is not for you!

I hope to answer all your question in the vein of "Is DBT the right tool for me?"

Analytics as Code is the core philosophy of the tool; Lower the barrier to use SQL collaboratively

DBT is authoring parameterized SQL code and using CI/CD to deploy it.

DBT functions as a compiler and a runner, while the database is responsible for execution. DBT package management system lets you re-use modular SQL in your project, drastically improving the time to finish line.

Enable data democratization; Let people discover and understand the history of their data

DBT ships data docs that allow users to search datasets they need.

People creating the tables and views can capture the context and meaning in YAML files. DBT cli converts this into a website where users of this data can see the lineage (a graph of source data to the end table) along with the meaning of the cols etc. This removes data silos between DEs, DAs, and DSs.

Automated deployments and isolated dev environments are baked in; Ease the toil of repetitive tasks for a happier team

Get the freedom to work without impacting users, use ENV vars and profiles.

All the code is configurable to the given environment. To achieve speedy deployment with a decentralized workflow, dbt makes development and deployment seamless. The team can even automate admin tasks like granting permissions on the new table programmatically using dbt hooks.

Data Quality is a first-class citizen; Enable the team to write and re-use tests for their data and schema

Standardize table schemas as the API for downstream users of your data.

DBT provides schema change and data quality tests out of the box. There are ~20 native tests and ~100+ community contributed tests. You can also get test and documentation coverage. It is as easy as adding some lines to a YAML file.

5000+ companies have adopted DBT as a core part of their data teams' workflow. Give it a try in your next data project!