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Google Storage\n2. Compute Instance \n3. BigQuery\n4. Looker Studio\n\nModern Data Pipeine Tool - https://www.mage.ai/\n\nContibute to this open source project - https://github.com/mage-ai/mage-ai\n\n\n## Dataset Used\nTLC Trip Record Data\nYellow and green taxi trip records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts. \n\nHere is the dataset used in the video - https://github.com/darshilparmar/uber-etl-pipeline-data-engineering-project/blob/main/data/uber_data.csv\n\nMore info about dataset can be found here:\n1. Website - https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page\n2. Data Dictionary - https://www.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf\n\n## Data Model\n\u003cimg src=\"https://github.com/ShubhamMohanty680/Uber_Data_Analysis/blob/main/data_model.jpeg?raw=true\"\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshubhammohanty680%2Fuber_data_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshubhammohanty680%2Fuber_data_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshubhammohanty680%2Fuber_data_analysis/lists"}