When large data volumes stream in continuously from variety sources with high velocity, unless you look closely and immediately, you can miss critical insights that are urgent for you to act on. With batch-mode analytics in Big Data or data warehouse solutions, by the time you gain operational insights, they are no longer actionable. Striim offers streaming analytics and processing capabilities to detect patterns and anomalies that matter to your business as they happen, and allows for immediate action.
Striim offers an end-to-end solution for real-time data integration, comprehensive streaming analytics, and data visualization to accurately discover critical, time-sensitive insights and enables automated response. Its ease-of-use enables fast time-to-market and easy modification of analytical applications. As a complete, enterprise-grade platform, it meets the strict security, reliability, and scalability requirements of business-critical solutions.
Power outages can have adverse outcomes, especially for households that have life-saving medical devices. TEDAS works with Striim to integrate real-time SCADA data from its energy distribution network and correlates with internet and phone service outage data in real time to immediately validate service needs for outages.
TEDAS also analyzes this outage info with households that operate highly-critical medical devices that cannot tolerate extended outage. With the ability to prioritize high-risk households for restoration service, it averts tragic outcomes.
Prevents tragic outcomes that may result from power outages by using real-time intelligence to prioritize service restoration efforts
Saves operational costs by using up-to-date and reliable information to avoid unnecessary service visits
Modernizes its data and analytics architecture to gain agility and to improve its public service with higher cost savings
Striim combines all relevant data and performs in-flight enrichment to obtain a comprehensive view into operations. By using filtering, multi-source correlation, advanced pattern matching, predictive analytics, statistical analysis, and time-window-based outlier detection via continuous queries on the streaming data, it identifies events of interests fast and accurately. In addition to sending automated alerts and triggering workflows, it publishes results to real-time, interactive dashboards, and distributes data to the rest of the enterprise.
Continuous Data Ingestion from a Wide Variety of Data Types Including IoT Data and Geolocation Data
Comprehensive Streaming Analytics with Advanced Pattern Matching, Predictive Analytics, Outlier Detection
SQL-Like Language and Wizards-Based Development to Easily Build and Modify Analytical Applications