Solutions

Solutions

TigerGraph empowers fast real-time analysis to solve the toughest Big Data problems.

Challenges

Cyberfraud is an immense threat for all e-commerce, especially for financial institutions and their customers. According to Gartner, 50% of online attacks target banks and eCommerce sites. From retailers small and large, to telecom and e-service providers, to financial institutions themselves, every type of business is targeted for fraud, with criminal methods tailored to each type of business. Criminals use extremely sophisticated, ever-adapting tactics to bypass traditional anti-fraud solutions. Many enterprises have access to the data that could reveal the illicit activity, but their traditional prevention and detection capabilities are proving to be too slow, too expensive, and generally incapable of analyzing the massive volume of customer, institution, and transaction data stored across various locations, formats, and protocols. The challenge is increasingly problematic due to strict regulatory compliance and growing data complexity.

TigerGraph Advantages

TigerGraph combats financial crime in real-time by allowing organizations to quickly deploy sophisticated anti-fraud capabilities and to evaluate proposed transactions before they are authorized.. Using the TigerGraph Native Parallel Graph with real-time Deep Link Analytics, enterprises can track and monitor each customer’s transactional behavior across numerous accounts and search out non-obvious and distant connections and patterns.

Challenges

In the Age of the Customer, the customer has access to more information than ever before. More importantly, the customer takes the lead in the engagement process and purchase experience. To keep up, organizations need to implement cross-channel customer strategies that ensure a consistent multipath purchase experience. They need to assemble a 360-degree view of their customers and transform it into actionable intelligence. Many organizations have been able to gather most of the needed data, but their traditional analytic technologies are proving to be too slow, too expensive, and generally incapable of deriving more sophisticated insight from the massive amount of customer, transaction, and external data. The challenge is exacerbated by increasing demand for marketing accountability, sales effectiveness and service quality.

TigerGraph Advantages

TigerGraph, with its DeepLink Analytics, enables customer intelligence in real-time by allowing organizations to quickly deploy powerful relationship analysis capabilities. Real-time capabilities allow retailers to quickly synthesize and make sense of customer behavior and activities. TigerGraph’s Native Parallel Graph creates a model where all customer data, internal or external, static or dynamic are stored and then connected, linked, and integrated. This creates a seamless and unified customer experience across all physical and digital sales channels. TigerGraph offers Start Kits to help you quickly achieve your complete customer user profiling customer lifecycle management solution.

Challenges

Global companies are managing multiple supply chains and they are dependent on those operations to not only deliver goods on time, but to respond to divergent customer and supplier needs. The difference between success and failure lies in the ability to reduce the risk of operational disruption, increase site reliability, improve supplier relationship management, and manage plant operations in a cost-effective manner. Many organizations have been able to gather most of the needed data, but their traditional analytic technologies are proving to be too slow, too expensive, and generally incapable of analyzing the massive volume of partner, route, transaction, and other data stored across various locations, formats, and protocols.

TigerGraph Advantages

TigerGraph delivers real-time visibility and analytics into key supply chain operations including order management, shipment status, and other logistics. Organizations can rapidly model their supply chain functions and business processes in real-time, through the use of a Native Parallel Graph data-compute graph. TigerGraph DeepLink Analytics enable advanced analysis and pattern recognition to identify product delays, shipment status, and other quality control and risk issues. Powerful event impact capabilities notify personnel when a relevant action has taken place and reveal the updated consequences down the chain, such as how a production slowdown impacts manufacturing, order fulfillment, pricing and revenue down the line. This fast, real-time insight allows them to optimize orders and shipping routes, and also quickly respond to changing demand patterns as events unfold. TigerGraph features high availability, system monitoring, and other enterprise readiness capabilities that ensure that real-time shipping status and other mission critical information is always available.

Challenges

From meter readings to the constant flow of information from sensors and network components, utilities companies are being flooded with data. But the vast majority of grid monitoring systems are many decades old with extremely limited visibility. Thus most utilities companies are very limited in their ability to plan, optimize, and respond to dynamic demand changes. This results in far more operational risks, higher costs, and more accidents. Some companies have tried to employ traditional business intelligence technologies to address the problem. But the data size and complexity are so large that traditional analytics have proven too slow, too expensive, and generally incapable of analyzing the massive quantity and complexity of energy and utilities data.

TigerGraph Advantages

Working closely with leading energy and utility companies, TigerGraph has pioneered Native Parallel Graph approaches that help companies monitor and analyze power flows, detect bottlenecks, and alert personnel about grid performance issues. Balancing a power grid requires solving a matrix equation for the whole graph, which is DeepLink Analytics taken to the extreme. Using real-time analytics on their Big Data, companies can respond immediately to events thus reducing operational risk and overall cost while improving safety, reliability, efficiency, and customer experience.