SAN CARLOS, Calif. & DENVER, Co.— March 27, 2012 — MarkLogic Corporation, the company powering mission-critical Big Data Applications around the world, today announced that Chris Biow, CTO, MarkLogic Public Sector, will speak at the 2012 Department of Defense Intelligence Information Systems (DoDIIS) Worldwide Conference taking place April 1 – 4, 2012 at the Colorado Convention Center in Denver, CO. Biow will present on the Joint Architecture Reference Model (JARM), a common framework and language for describing how the Intelligence Community conducts business. Biow will describe major Community information system efforts in terms of the JARM framework, including cutting-edge systems that will enable cloud-based access to large amounts of intelligence data with the ease of a commercial smartphone app.
DoDIIS is hosted annually by the DIA Directorate for Information Management (DS) and Chief Information Officer (CIO). This year’s theme, “Advancing Mission Integration,” will highlight the DIA CIO’s commitment and intent to unify defense intelligence infrastructure and information sharing initiatives. Biow’s “JARM View of DI2E and Data Cloud Frameworks” breakout session is scheduled for 12:45 PM to 1:30 PM on Monday, April 2 in Room 407 at the Colorado Convention Center.
MarkLogic will be demonstrating two real-time applications at the conference including a real-time message-handling application and a social media analytics platform at booth #811.
“MarkLogic is delighted to host a breakout session at this year’s DoDIIS Conference,” Biow said. “We have a great deal of experience addressing the unique data challenges faced by the Intelligence Community as they migrate to new tools, platforms, and programs to improve mission effectiveness. MarkLogic’s experience in the Intelligence Community and this presentation will benefit conference attendees who are looking for better ways to access and utilize Big Data in cloud environments.”
MarkLogic helps customers create value from complex data faster. Our platform ingests data from any source, creating and refining metadata to support powerful models. Customers use these models for deep search and query, building enterprise applications and bringing unique insights to analytics and machine learning.
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