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data-engineering-zoomcamp
ghcn-d | data-engineering-zoomcamp | |
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1 | 119 | |
21 | 22,673 | |
- | 2.8% | |
10.0 | 9.4 | |
over 1 year ago | 19 days ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU General Public License v3.0 only | - |
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ghcn-d
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Celebrating my first Data Engineering Project -- Fitbit data with PySpark, GCP, prefect, and terraform!
MarcosMJD Global Historical Climatology Pipeline
data-engineering-zoomcamp
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Data Engineering Zoomcamp Week 6 - using redpanda 1
References: Data engineering zoomcamp week 6 course and homework notes: https://github.com/DataTalksClub/data-engineering-zoomcamp/tree/main/cohorts/2024/06-streaming
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Final project part 5
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.
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Building a project in DBT
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.
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Testing and documenting DBT models
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.
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Extracting data with dlt
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.
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Data engineering at home?
Take a look.DE zoomcamp
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Rockstar Data Engineers making big bucks: what are you doing exactly?
If you need guidance you can attend the data engineering zoomcamp, it's free and quite solid.
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Self study material
Welcome. Start with Data Engineering Zoomcamp, try and build a project, see if you like it, then continue to get into deeper resources.
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What is the best way to learn Python if I want to become a data engineer
Can take a look at this - https://github.com/DataTalksClub/data-engineering-zoomcamp
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Course Recommendations for a New Grad
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
What are some alternatives?
audiophile-e2e-pipeline - Pipeline that extracts data from Crinacle's Headphone and InEarMonitor databases and finalizes data for a Metabase Dashboard.
mlops-zoomcamp - Free MLOps course from DataTalks.Club
data_engineering_project_1 - My first attempt at a rough ETL pipeline; technologies include spark, GCS, prefect orchestration, and terraform
Cookbook - The Data Engineering Cookbook
steam-data-engineering - A data engineering project with Airflow, dbt, Terrafrom, GCP and much more!
AdventureWorks - Projects using the AdventureWorks database
automate-dv - A free to use dbt package for creating and loading Data Vault 2.0 compliant Data Warehouses (powered by dbt, an open source data engineering tool, registered trademark of dbt Labs)
versatile-data-kit - One framework to develop, deploy and operate data workflows with Python and SQL.
Reddit-API-Pipeline
udacity-capstone
DataEngineerZoomCamp - I'm partaking in a Data Engineering Bootcamp / Zoomcamp. I'll store files and progress here.
Think-Python-2E-My_solutions - My solutions to the exercises contained in the "Think Python 2nd Edition" book by Allen B. Downey.