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Collated over 20 million records with information acquired through web scraping and APIs with python to identify which locations were not meeting the educational needs of their population. Then made an application in Tableau for a user to explore the findings.

Technologies used: Python, Tableau, PostgresSQL

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Used PostgreSQL to query over 14 million records in order to find trends then presented findings in Tableau by creating an interactive dashboard providing recommendations. Additionally created an heartbeat monitor that allows the user to specify how they would like there usage data to be broken down. This ranges from year, month, week, day of the week, day of the month, and hour of the day including the intersection of the categories; as well as by station or even by popular route. For example they could find what was the quantity of rides at 1 pm on July 4th 2017 between stations 45 and 64, or anything less specific.

Technologies used: PostgreSQL,Tableau

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Explored the intricacies of the wind farm market in order to provide insights for potential investors. Researched the regulations and policies and their effect on revenue. Provided potential recommendations for operators to invest in. Transformed data from the National Oceanographic and Atmospheric Administration in order to map wind resources

Technologies used: Python, Tableau 

click here to see dashboard

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