amazon-emr-with-delta-lake
data-engineering-zoomcamp
amazon-emr-with-delta-lake | data-engineering-zoomcamp | |
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1 | 119 | |
17 | 22,562 | |
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4.0 | 9.4 | |
6 months ago | 15 days ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT No Attribution | - |
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amazon-emr-with-delta-lake
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?
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
mlops-zoomcamp - Free MLOps course from DataTalks.Club
ngods-stocks - New Generation Opensource Data Stack Demo
Cookbook - The Data Engineering Cookbook
demo-code - Bits of code I use during live demos
AdventureWorks - Projects using the AdventureWorks database
BigDL - Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with llama.cpp, Ollama, HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, etc.
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.