The client wanted to group multiple restaurants onto a single social marketplace. To achieve this, they wanted to pull restaurant-specific information from various social networking sites like Instagram, Foursquare and Twitter. They had targeted to fetch & store the metadata of more than 27,000 restaurants. This huge data had to be analyzed for which the client required an analytics system. In addition, the data of these restaurants had to be updated in the system on a daily basis An important challenge was to understand the APIs of Instagram, Foursquare, Twitter in order to read the restaurant’s metadata. The client's requirement was to rapidly process data from the thousands of restaurants on a daily basis. Moreover to handle this huge data, client wanted to implement Big Data analytics.
PBS successfully brought more than 27,000 restaurants onto single marketplace through the Big Data on Microsoft Azure solution. Our team developed an architecture that handles Big Data from social networking sites like Foursquare, Instagram, & Twitter. We leveraged worker role to take care of background processes and Azure tables for storing data.
APIs were developed based on ASP.NET Web API, which is a powerful platform for building RESTful applications on the. Net framework. The system enables secured authentication and we used Telerik platform to leverage data analytics. We also built high performance web APIs to be consumed by external
