The recent terror attacks in Brussels have issued a fearful reminder of the dangers travelers continue to face, but the war against terrorism continues both by governments and private enterprise. A case in point? Presicent Traveler, which uses in-memory analytics in an application for traveler safety.
Prescient Traveler is built in part on SAP's HANA in-memory platform, which provides the real-time capabilities demanded by an effective travel safety application, as Constellation Research VP and principal analyst Holger Mueller writes in a newly published case study:
Despite a shift to a digital world, globalization forces enterprises to operate at an increased level worldwide, and that trend is only growing. As a result, enterprises need to dispatch employees more often and farther than ever before into all parts of the world. Prescient Traveler is solving the challenge of identifying the risks employees may be exposed to on their travels.
Traveler ingests information about safety risks, which can also include factors such as severe weather and erupting civil unrest, and delivers alerts to users through a smartphone application.
Prescient was founded by former intelligence, special operations, law enforcement and business professionals and has focused on solving problems around risk mitigation, due diligence, training and research.
When developing the traveler safety application, Prescient first pinpointed Hadoop as an appropriate back-end data store, but soon realized it needed something else to complete the application, as Mueller writes:
The point of contention quickly came to the machine-based curation of risks and their classification by severity and their attribution to individual travelers. It was clear that these challenges could only be solved through a highly reliable, high throughput database. After a search and some trials, the product team found SAP HANA. Not only was it able to store risk information, but it also enabled both manual and machine-based curation of risk.
As a bonus, HANA’s geo-spatial capabilities not only allowed for the attribution of risks among each other, but also a highly efficient and in-memory fast attribution of risks to travelers. Moreover, analysts can model “elevated threat zones” and inform travelers efficiently of their proximity. Any new risks appearing are directly attributed and correlated to other already known risks. Knowing real world distances between different risk events and episodes is immensely valuable for both the machine-based and human-enabled curation of risks.
Other benefits of HANA include its sentiment analysis capabilities, which Prescient uses to sift through event-related messages in many languages and extract meaning.
Mueller outlines several important takeaways for CxOs in the full case study, some of which include the following:
Orchestration beats single sourcing. In order to tackle today’s system requirements, a single solution from a single vendor cannot provide the complete solution. Prescient uses multiple vendors for building the complete traveler safety solution. A similar capable and affordable solution would not have been possible with a single-sourced technology stack.
CxOs building next-generation applications such as this traveler safety system should consider a number of recommendations.
First, thinking of next-generation capabilities as a design point is crucial for success. Had the Prescient product team not demanded and kept searching for an in-memory, real-time platform, it may not have found SAP HANA. The result would have been a clearly subpar application. Technological progress enables constant improvement.