Opturo’s Web Services offer a way for a client to request data by making a HTTP call to a server. The server processes the call and returns the data requested by the client based on a specific set of requirements. The data can be returned in a variety of formats based on the client’s need. Examples of formats are JSON, XML, CSV and Delimited. Files including PDF, ZIP, XLSX can also be returned by a web service. Web Services also can ingest data sent from the client. Client data relevant to the process passed in through a web service call can be processed and used in the analysis reporting.
VIA provides the foundational platform and a turnkey approach to quickly creating and deploying new web services. Any data, analysis and report can be made available in real-time to clients through a secure connection.
New custom web services are created quickly using Opturo’s VIA IDE Application which leverages the robust data management/custom solution building functionality of the VIA Platform.
The VIA platform offers a powerful analytical library including Matlab which can be leveraged to offer value-added analytical services to current clients.
Flexible output options including JSON, CSV and XML allow for quick integration with any system.
Opturo’s various analytical solutions can be implemented in a fraction of the time of competing systems, as we leverage each client’s unique infrastructure. Data formatting, replication and synchronization issues can be minimized or eliminated with an Opturo implementation.
Users may select the language they prefer when utilizing the platform, which includes the web-based GUI and reports exported into PDF files. Don’t see your preferred language in those we offer? We are able to rapidly add client requested languages that are not currently supported.
Opturo’s innovative architecture provides clients with a platform which can be scaled to meet the needs and scope of any project. Whether leveraging significant proprietary data infrastructure or going to the cloud, Opturo can help the largest enterprises address their big data challenges.