AnalyticsXtreme, offered as part of the InsightEdge platform, powers insight-driven organizations to address time-sensitive business decisions with smarter and faster analytics. AnalyticsXtreme accelerates access to data lakes and data warehouses by 100X and simplifies development and deployment of applications for faster time to market on-premise and in the cloud. Applications can leverage real-time machine learning and deep learning models on both hot mutable data combined with historical data which is stored in data lakes and data warehouses from a unified API. This provides a single logical view of data that is spanned across real-time and historical data platforms, including SQL, Spark dataset/dataframe as well as BI tools, like Tableau and Looker.
AnalyticsXtreme in-memory performance powers:
Unified API access accelerates development and deployment while ensuring data consistency:
AnalyticsXtreme simplifies the complexities of the Lambda architecture for:
Intelligent tiered storage capabilities deliver business-driven policies to automatically auto-tier hot and warm data between RAM, Persistent Memory, Storage Class Memory and SSD, as well as automatically move data for cold storage, and archiving to data lakes and data warehouses.
By utilizing these advanced mechanisms for intelligent tiering, data is efficiently stored in the right storage layer based on performance, while optimizing infrastructure costs across the entire solution and data lifecycle.
Customer
This airline is one of the largest airlines in the world, with thousands of flights per day to hundreds of destinations in more than 50 countries, serving around a million passengers each day.
Business Challenge
This airline needed to leverage mass amounts of data from the served airports to optimize logistics concerning resources, fight plans, crews, etc. – especially upon unplanned changes,for rapid accurate response. They required to ingest real-time data from multiple applications and data sources and analyze the data to optimize operations and pricing.
Technical Challenge
Solution
With GigaSpaces’ in-memory real-time analytics platform, this customer was able to predict and instantly handle any change in the scheduling and operating workflow. The platform’s event triggers analytics and machine learning and leverages data ingested and aggregated such as fuel costs, weather, news and more. The ability to access historical data, such as past delays during peak traffic, enriches the insights gleaned and increases the accuracy of the delay probability.
Customer
This leading rail-based transportation company is focused on rail transportation and real estate, supplying rail-based freight transportation. Their rail and intermodal businesses provide rail-based transportation services including traditional rail service and the transport of intermodal containers and trailers.
Business Challenge
This customer needed to run predictive analytics on their equipment while ingesting and processing streaming data at scale, in order to monitor and diagnose potential failures to help its fleet operators reduce maintenance costs, improve the process of troubleshooting, and redirect trains in a timely manner.
Technical Challenge
Solution
With GigaSpaces’ in-memory real-time analytics platform, this customer was able to ingest and process streaming data from millions of sensors and provide real-time insight and respond instantly to situations. By leveraging machine learning on real-time and historical data, the safety and reliability of the journey has improved as well as cost-saving measures that conserve fuel and increase safe operating speeds. Event-based triggers now direct the output to operational workflows and live dashboards for timely maintenance and redirecting of trains.
Customer
A leading department store retail chain offers exclusive and national brand apparel, shoes, accessories, beauty and home products with stores across the United States
Business Challenge
Retail organizations not only want to improve their eCommerce traffic but also their business via Brick and Mortar shops. Traditional architectures have challenges supporting hundreds of thousands of users and promotions. This customer wanted to shift to modern architectures is via a transitional strategy.
The customer also wanted to implement machine learning and analytics for location-based advertising in order to provide its customers with location-based recommendations in real-time.
Technical Challenge
Solution
With GigaSpaces’ in-memory real-time analytics platform, this customer was able to increase in-customer visits to stores, in purchase volume (in $) for coupon-based customers, and in coupon usage (in %) by customers.
Customer
This company is a leader in fraud prevention and risk management. They provide financial institutions and customers with fraud and risk management tools, facilitate a secure exchange between financial organizations and offer solutions for responding quickly to evolving fraud challenges.
Business Challenge
This customer was looking for a solution to detect fraud in real-time for mobile payments and check deposits. They required high-availability to assure 24X7 access for demanding customers. Reducing their current TCO was also a priority.
Technical Challenge
Solution
The GigaSpaces in-memory real-time analytics platform provides sub-second response for accurate fraud detection to stop the transaction before it is completed. The high-performance solution ingests 4 TB daily and handles over 1.5M events per second. TCO was reduced when introducing RAM and SSD, replacing expensive alternatives. No-Downtime is assured with a fault-tolerant, highly available, scaling on-demand solution.
