versatile-data-kit VS data-engineering-zoomcamp

Here's the project: https://github.com/vmware/versatile-data-kit

I don't really know if this would work for you because the UI is not functional yet, but a very simple REST API ingestion example here, there's one for csv too https://github.com/vmware/versatile-data-kit/wiki/Ingesting-data-from-REST-API-into-Database I can't imagine a simpler way unless it's really drag and drop.

I work at VMware and we use one tool for the whole ELT, it was made internally as there was no good alternative at the time and now we opensourced it, here it is: https://github.com/vmware/versatile-data-kit

With my team we created csv ingestion plugin described here, maybe you want to try it out: https://github.com/vmware/versatile-data-kit/wiki/Ingesting-local-CSV-file-into-Database

We use Versatile Data Kit for batch data job orchestration (https://github.com/vmware/versatile-data-kit)

"suggestions on how to reduce the time spent on initially generating and adjusting the code" is using some tools that automate ELT. Here's one open-source tool I'm working on with my team: https://github.com/vmware/versatile-data-kit

here's the repo: https://github.com/vmware/versatile-data-kit

If you wish to contribute, projects usually have good first issues: https://github.com/vmware/versatile-data-kit/labels/good%20first%20issue If you wish to learn, check out examples: https://github.com/vmware/versatile-data-kit/tree/main/examples

Have you heard about versatile data kit (https://github.com/vmware/versatile-data-kit)? I think it meets your needs perfectly:

Versatile Data Kit is a framework to bBuild, run and manage your data pipelines with Python or SQL on any cloud https://github.com/vmware/versatile-data-kit here's a list of good first issues: https://github.com/vmware/versatile-data-kit/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22 Join our slack channel to connect with our team: https://cloud-native.slack.com/archives/C033PSLKCPR

References: Data engineering zoomcamp week 6 course and homework notes: https://github.com/DataTalksClub/data-engineering-zoomcamp/tree/main/cohorts/2024/06-streaming

dbt is the main part of my data engineering project for Data Talks Club's data engineering zoomcamp. After a few frustrating errors on my part, I finally figured out how to make models, where to put the staging models and where to put the core models, how to compile a seed file, and how to join it to the main file in order to produce data for visualization. I also used the git interface to continually upgrade my repository. This was extremely convenient and helpful.

For Week 4 of DataTalksClub's data engineering zoomcamp, we had to install dbt and create a project. This was a formidable task. dbt is a data transformation tool that enables data analysts and engineers to transform data in a cloud analytics warehouse, BigQuery in our case. It took me a very long time to do this, and in this case I needed the homework extension.

In this video we learned how to test and document dbt models. We also learned about the codegen library. This is part of Week 4 of the data engineering zoomcamp by DataTalksClub.

If you want to run these commands yourself, either in a Jupyter notebook or in Google Colab, you can get the file from HERE. You can get an overview of the workshop HERE. When I ran in a Jupyter notebook, I had to delete the first line (%%capture) and put quotes around dlt[duckdb] in the second line.

Take a look.DE zoomcamp

If you need guidance you can attend the data engineering zoomcamp, it's free and quite solid.

Welcome. Start with Data Engineering Zoomcamp, try and build a project, see if you like it, then continue to get into deeper resources.

Can take a look at this - https://github.com/DataTalksClub/data-engineering-zoomcamp

I think you can start with something free with this pretty practical course on Data Engineering from DataTalksClub - https://github.com/DataTalksClub/data-engineering-zoomcamp