big data/ AI

I'll share the experiences and lessons learned during the process of Salesforce data intelligence platform shifting from private data centers to public cloud. I'll share (1) why public cloud, the vision of our cloud data ecosystem (2) distilling requirements of the data platform from user personas and scenarios (3) designing the technical architectural blueprint based on principles (4) critical decision making processes around regions, network, security, multi-tenancy, data catalog, data governance, cost etc (5) roadmap planning and milestones design (6) Related AWS and GCP data ecosystems
Who is this presentation for?

Prerequisite knowledge:
big data ecosystem
What you'll learn?
Methods and approaches of shifting enterprise data ecosystem to public cloud: vision-> requirements-> architecture-> execution

Conan is a Director TPM and system architect at Salesforce Data Intelligence team. His PhD area is parallel database algorithms on GPUs. He has worked on SQL Server, Azure and Office big data systems at Microsoft, and on infra big data architectures at Salesforce.