Case Study: a US restaurant chain improves customer segmentation with Flatworld Solutions' NoSQL-to-SQL plugin and predictive algorithm

a US restaurant chain segments customers with Flatworld Solutions using a flexible NoSQL-to-SQL plugin

The US restaurant chain wanted to utilize its large volume of unstructured data stored in MongoDB but found its NoSQL architecture limiting for building predictive models. They approached Flatworld Solutions for a solution that could effectively convert this data into a more analyzable format.

Flatworld Solutions designed a generic plugin to convert the complex NoSQL data into SQL. They then built a predictive algorithm on this data, which efficiently segmented the restaurant's customers. This solution provided the client with the flexibility to make essential business updates.