A novel system architecture for online operational analytics

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Database management systems promised not only persistent storage of transactional data but also their fast and timely (ideally real-time) analysis to support business critical applications. However that promise has always been out of reach due to practical constraints in software and hardware. As a result a typical business data infrastructure is divided between a database transactional store, for "live" business data (e.g. sales, leads, and other opportunities) plus an operational data warehouse for analysis and decision-making. The data images in these two datastores are not in sync, typically lagging by weeks or months.** Recent technological advances are finally converging to bring a unified system within reach, including enormous main memories; highly parallel multi-core processors; fast, high-bandwidth storage systems using solid state disks; and widespread availability of field-programmable custom hardware. The proposal explores a new platform---to be designed from the ground up---that will leverage these new technologies in support of sophisticated, real-time analysis of complex and evolving data, generated by mission-critical systems and business processes. The main emphasis will be around software-hardware co-design to reap the benefits of modern hardware technologies and offer increased performance capable of meeting real-time operational analytics goals. The proposed architecture and system will rely on the solid foundations of the relational data model and SQL and offer self-management and power efficiency, while its real-time capabilities bring true convergence of transactional data and operational analytics.** This research will enable businesses to make real-time decisions on strategy and key functions such as marketing, reacting on business KPIs such as sales in a timely fashion. It will enable delivery of new applications in a world that is struggling to understand and manage big data, such as novel advanced sensing applications and real time medical applications. Finally the work will produce highly qualified personnel in an area of strategic importance to the country such as the management and analysis of big data.