Quartet FS
Real Time Insight Into Business Operations

Real-time visibility into business activities is crucial for the successful operation of any organization. Recognizing this requirement, Georges Bory, Xavier Bellouard, Kathy Perrotte, Jean Safar and Allen Whipple, founded Quartet FS, an in-memory analytics technology provider. Quartet FS enhances the free exploration of data across various dimensions and provides business users real-time insight into large volumes of data. Real-time visibility into their business ensures that business users can take actions that translate into better performance and better agility for their organization. Users can analyze sophisticated performance indicators and extract actionable intelligence from massive amounts of complex data, which enables them to make informed decisions in a timely manner. Data is extracted in its native format, then stored and manipulated using in-memory Javabased computing capabilities. This is followed by sophisticated calculations on huge data volumes, without the support of data transformations and duplications. Performance indicators are recomputed on the fly as soon as a change occurs in the source data. Eventually business users are able to analyze data at various levels of detail and across as many dimensions as they need at lightning speeds. They can also run simulations in realtime in order to assess the impact of their decisions.

Kathy Perrotte, MD and co-founder at Quartet FS comments about the company’s solution, ActivePivot, an in-memory analytics database with advanced data aggregation capabilities. “The implementation of distributed architecture into the ActivePivot solution enables massive amounts of data to be analyzed faster, from multiple global sites. We built the solution to meet direct customer demand for in-memory analytics with distributed architecture capabilities, so that CIOs can adopt ActivePivot for large deployments with confidence that the technology can grow with their data and provide revolutionary improvement in end-to-end performance.

Organizations can now maximize the potential of distributed architecture and large heap size to explore new use cases across different business sectors.”

Quartet FS supports operational decision-making across critical areas, such as predictive analysis, management by exception, impact analysis, resource optimization, crisis management, and collaboration. Quartet FS’s solutions are suited to time-sensitive and data-intensive business processes which include risk management, supply chain management, regulatory compliance, fleet management, e-commerce traffic optimization, dynamic pricing, fraud detection, real-time bidding, online media trading and revenue leakage. Quartet FS has historically worked largely with financial institutions, one of the most demanding sectors when it comes to Big Data analytics, but also offer services to many other industries, including e-commerce, transportation, logistics, media and telecommunications.

For instance, in logistics, one of the biggest drivers is supply chain agility. This requires an end-to-end visibility across the entire supply chain. The problem is that supply chains are getting more and more global and are involving an evergrowing number of stakeholders. This is a key challenge for a number of multinational companies with dispersed operations across several continents, regions and countries. In these organizations, data is scattered across a huge amount of systems that don’t interoperate. Acting as a control tower for the supply chain, ActivePivot helps logistic service providers get an endto- end visibility across all these departmental silos through a dashboard presenting meaningful KPIs. Moreover, the system monitors thresholds in real-time through its event monitoring feature, which allows users to react to unexpected or disruptive events. Steered by a group of entrepreneurs, with expertise in building software for the capital markets sector, Quartet FS endures to focus on the powering of a new generation of applications that support operational decision-making in today’s Big Data era.