Abstract: System and method embodiments are provided for implementing Data as a Service (DaaS). The system is implemented using a client side library, on a user device, and a server or proxy server to extract relevant data from relevant data sources, and process the data before returning results to the client. The client sends a user query to the proxy server, which then sends sub-queries and receive responses from multiple data sources in real-time or near real-time. The system also uses a data model that handles varying data reliability or accuracy levels in heterogeneous data sources and indicates the confidence levels in the data provided to a user or client application. The data model assigns different confidence levels for various data to distinguish between high quality data and low quality data. Thus, users are provided with more information from multiple sources without diluting high quality data with low quality data.

Abstract: System and method embodiments are provided for implementing Data as a Service (DaaS). The system is implemented using a client side library, on a user device, and a server or proxy server to extract relevant data from relevant data sources, and process the data before returning results to the client. The client sends a user query to the proxy server, which then sends sub-queries and receive responses from multiple data sources in real-time or near real-time. The system also uses a data model that handles varying data reliability or accuracy levels in heterogeneous data sources and indicates the confidence levels in the data provided to a user or client application. The data model assigns different confidence levels for various data to distinguish between high quality data and low quality data. Thus, users are provided with more information from multiple sources without diluting high quality data with low quality data.