NYC Taxi Trip and Fare Data Analytics using BigData
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Authors
Patel, Umang
Chandan, Anil
Issue Date
2016-04-01
Type
Presentation
Language
en_US
Keywords
Big data , Data analysis , New York , Taxi
Alternative Title
Abstract
Traditionally the data captured from the NYC Taxi & Limousine commission was physically analysed by various analyst to find the superlative practice to follow and derives the output from it which would eventually aids the people who commute via taxis. Later during early 2000 the taxi services where exponentially developed and the data capture by NYC was in GB’s, which was very difficult to analyse manually. To overcome these hitches BigData was under the limelight to analyse such a colossal dataset. There were around 180 million taxi ride in city of New York in 2014. BigData can effortlessly analyse the thousands of GB within a fractions seconds and expedite the process. This data can be analysed for several purposes like avoiding traffics, lower rate where services are not functioning more frequency than a cab on crown location and many more. This information can be used by numerous authorities and industries for their own purpose. Government official can use this data to deliver supplementary public transport service. The company like Uber can use this data for their own taxi service.