Streaming Cloud Analytics

CASE STUDY


Our streaming cloud analytic solution quickly processes high velocity data for real-time queries in the cloud.  This demonstration ingests complex XML files, each containing 5000-7000 ship reports, and displays the latest ship positions in real-time.  In addition, users can select individual ships to retrieve historical location data, including the most recent position.  There system process over 1000 XML files, ingesting one file every five seconds.

To handle this workload, we've built a system implementing our iNovex Lambda architecture.  This architecture combines stream processing and cloud storage to quickly publish data for end-user consumption.  The stream processing and cloud storage systems scale horizontally to cope with big data requirements.

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Semantic Data Integration

 CASE STUDY


 In the current state of technology, applications query sets of pre-defined data sources. When a data schema changes, application logic (e.g. business rules) and presentation logic must change. This brittle architecture delays the delivery of business capabilities, and greatly increases labor costs. Further, queries are written to specific databases; therefore the entire set of available databases and other content repositories are not considered. Although the answer to a basic question may reside in the “system”, the query will never know.  There exists vast, untapped knowledge potential in stand-alone databases and data sources.  When viewed separately, these databases each possess intrinsic value to those who understand them. 

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Unified Information

CASE STUDY


  Our unified Information Access prototype processes unstructured content through text annotation tools of choice, and integrates annotated content with structured data.  Developers can configure these tools to perform entity and relationship extraction, categorization, sentiment analysis, and more.  Customer or open source services can be plugged into the framework as required.  The framework then processes extracted information through an array of annotation services that developers can configure to filter, alter, and enrich the data, for example by querying external data sources for additional metadata.

Read more: Unified Information

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