mdh266 / AirflowETL
Blog post on ETL pipelines with Airflow
☆23Updated 4 years ago
Alternatives and similar repositories for AirflowETL:
Users that are interested in AirflowETL are comparing it to the libraries listed below
- Example of an ETL Pipeline using Airflow☆34Updated 7 years ago
- Data models, build data warehouses and data lakes, automate data pipelines, and worked with massive datasets.☆13Updated 5 years ago
- PyConDE & PyData Berlin 2019 Airflow Workshop: Airflow for machine learning pipelines.☆46Updated last year
- (project & tutorial) dag pipeline tests + ci/cd setup☆86Updated 4 years ago
- Powerful rapid automatic EDA and feature engineering library with a very easy to use API 🌟☆53Updated 3 years ago
- ☆18Updated 3 years ago
- A tutorial that helps Big Data Engineers ramp up faster by getting familiar with PySpark dataframes and functions. It also covers topics …☆20Updated 3 years ago
- How to use Python to understand data and transform the data into a tidy format ready to be used for modelling and visualisation.☆37Updated 5 years ago
- A code-based tutorial for production level data streaming with PySpark plus Optimus for data cleaning, Confluent Kafka, & Apache Drill u…☆26Updated 5 years ago
- ☆19Updated 3 years ago
- Explore tips and tricks to deploy machine learning models with Docker.☆13Updated last year
- A modern ELT demo using airbyte, dbt, snowflake and dagster☆27Updated 2 years ago
- Work for Mastering Large Datasets with Python☆18Updated 2 years ago
- Automated Exploratory Data Analysis. Simplifying Data Exploration☆34Updated 4 years ago
- ☆16Updated last year
- Code snippets and tools published on the blog at lifearounddata.com☆12Updated 5 years ago
- Ingest tweets with Kafka. Use Spark to track popular hashtags and trendsetters for each hashtag☆29Updated 8 years ago
- Build your feature store with macros right within your dbt repository☆38Updated 2 years ago
- ☆11Updated 3 years ago
- The goal of this project is to offer an AWS EMR template using Spot Fleet and On-Demand Instances that you can use quickly. Just focus on…☆26Updated 2 years ago
- Pyspark in Google Colab: A simple machine learning (Linear Regression) model☆36Updated 5 years ago
- Full stack data engineering tools and infrastructure set-up☆50Updated 4 years ago
- ☆84Updated last year
- Demo on how to use Prefect with Docker☆25Updated 2 years ago
- Cost Efficient Data Pipelines with DuckDB☆49Updated 7 months ago
- Extracting LinkedIn comments from any post and export it to Excel file☆23Updated 6 years ago
- Instant search for and access to many datasets in Pyspark.☆34Updated 2 years ago
- Capturing model drift and handling its response - Example webinar☆107Updated 5 years ago
- ☆46Updated 2 years ago
- Source code for the MC technical blog post "Data Observability in Practice Using SQL"☆36Updated 7 months ago