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bigdataproject

Aim of the project is to build a historic flight data repository which includes collecting data and merging it so as to make a huge(big-data) dataset. The project includes four major tasks or modules. These are Data Cleaning, Data Integration, Search Engine and Data Analysis and Visualisation. First the data that has been collected from multiple sources need to be cleaned and the attributes are normalized. A new sub-module of Airline Ranking is added to the project. This is a part of Data Cleaning and Integration. In this part, the different airlines are ranked on the basis of delays they have made over the years. This is used by the search engine in order to recommend the flights. The search engine takes the details about the flight and searches the big data in order to retrieve the results faster. Two databases, AsterixDB and MongoDB are used for this purpose. The last module analyses the clean data and visualizes it in order to get clear insights on the data.

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