dbt vs. Panoply

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

Panoply is well suited for companies with large amounts of data that do not want all users of the company to see or view. It is appropriate for companies that have to store data for several years in case clients need the data. It is not made to constantly be downloading or looking at the documents.

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

• Ease of data integrations. Importing data into the data warehouse is a point-and-click effort.
• Automated data modeling. The data is modeled in a way that facilitates analysis without having to look into it myself.
• Query speed. Automated query optimization has really sped up our dashboards.

• 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

• The user interface could use some improvement for analytical tools. Apart from that, it’s great.

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

It’s a good choice for building a quick, multipurpose data stack for a variety of businesses needs.

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

Panoply has much more storage and better organization tools for searching. There are better folders and tools for keeping documents secure and stored for a long period of time. It is better to offload data in mass than singular or Zip drive documents like you would do in Google Drive.

Incentivized

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

Incentivized

• Saved time on Redshift setup
• Saved support costs (monetary and temporal) by not having to set up on-premise
• Widens the BI tool use in organization; lowers the barrier to entry and makes organization more productive in analytical terms