ZipCodeCore · nortonlyr · Apr 3, 2020 · Apr 3, 2020 · Apr 3, 2020 · Apr 3, 2020
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 # Airflow Project
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+![description_if_image_fails_to_load](https://github.com/nortonlyr/DataEngineering.Labs.AirflowProject/blob/master/Airflow_project_Updated050520.png)
+
+Question? 
+- How to select the valuable airbnbn home when travel to the NYC?
+
+Goal: 
+- Applied the Apache Airflow directed acyclic graphs (DAGs) to build data pipelines on NYC open data (park, shooting, hot_spot, hotel, public housing) and Airbnb housing data, followed by data minipulation, analysis, and visualization.
+
+
+Flowchart
+- Original sources: NYC OPEN DATA, Airbnb dataset (from Insider Airbnb)
+
+- Get requests and download the sources 
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+- Preliminary Data cleaning and manipulation 
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+- Import to SQL database (MySQL/PostgreSQL)
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+- Load data from database, and use jupyter notebook to show analysis and visualization (run in both localhost and AWS (EC2, RDS, S3))
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+
+![description_if_image_fails_to_load](https://github.com/nortonlyr/DataEngineering.Labs.AirflowProject/blob/master/airflow_flow_chart.png)
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