Market Surveillance with AI & Machine Learning

Streaming Data

Business runs in real time, and business-critical data from client or system transactions, streaming data from markets, supply chain, or vendor services, organizations need to analyze changing conditions and respond in real time.

Transactions involving significant data access or manipulation require optimized presentation/delivery of the data to the user or system controlling the transaction and providing analytics. In many cases this involves transaction processing at multiple nodes simultaneously or in series, requiring optimal data aggregation and transit.

Increases in distributed cloud-hosted Software (SaaS) and Platforms (PaaS) extends dispersed transaction data stored remotely from the event initiation node and from the compute processing incidence.

As parallel multi-processor times improve, this escalates transaction volumes, but data retrieval, return, visualization and replication can result in transaction delay experiences. Lintu helps you profile your total transaction landscape and choose the right technologies to assure optimal application and analytic performance.