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Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

Accelerate analytics and AI innovations with Intel (sponsored by Intel)

9:259:35 Thursday, 25 May 2017
Sponsored keynote
Location: Auditorium
Average rating: **...
(2.16, 19 ratings)

We are in an era of big data, analytics, and artificial intelligence. Intel’s vision is to provide the easiest, most secure, and most performant environment for its data customers and partners, from software to silicon. With AI becoming the next big wave in computing, many customers are adding AI workloads to their big data environment.

Ziya Ma outlines the challenges for applying machine learning and deep learning at scale and shares solutions that Intel has enabled for customers and partners, highlighting the BigDL Apache Spark project that Intel has recently open-sourced. BigDL is a unified analytics platform that can directly run on top of existing Spark or Hadoop clusters, giving customers a consistent and integrated experience for the entire learning process. Along the way, Ziya explains how Intel optimized solutions to help cloud businesses, financial services, manufacturing, and other companies to gain more insights and drive business differentiation and points to future trends and work in the space.

This keynote is sponsored by Intel.

Photo of 马子雅 (Ziya Ma)

马子雅 (Ziya Ma)


Ziya Ma is the vice president of architecture, graphics, and software as well as a director of data analytics technologies in system software products at Intel. She’s responsible for optimizing big data solutions on the Intel architecture platform, leading open source efforts in the Apache community, and bringing about optimal big data analytics and AI experiences for customers. Her team works across Intel, the open source community, industry, and academia to further Intel’s leadership in big data analytics. Ziya is a cofounder of the Women in Big Data Forum. At the 2018 Global Women Economic Forum, she was honored as Women of the Decade in Data and Analytics. She holds a master’s degree and PhD in computer science and engineering from Arizona State University.