I want to implement Big Data Analytics to bring thousands of restaurants onto a common social marketplace.

Our Results

Our client grouped successfully 27000+ restaurants onto a common social marketplace from the data of Foursquare, Instagram, & Twitter social networking groups by leveraging Microsoft Azure Cloud services.

Read More

Discuss Your
Business Challenges

Talk to Our Azure Experts

View Other Case Studies

Business Need

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.

Technology Solution

Microsoft Azure, MVC, Azure Tables, ASP .NET Web API

Saviant 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 platforms. These APIs fed data to the Google Marketplace platforms for restaurants.

Big data implementation case study

Looking to build Analytics driven Enterprise-grade Applications?
We can Help!

Connect with Experts