The most essential data event of 2017 – the flagship Big Data Innovation Summit is returning to San Francisco to help you…’
“Cultivate the Data, Become the Master, Yield the Profit“ Sow the seeds of your data success by becoming versed in the most efficient and secure storage strategies from industry forerunners in San Francisco this April 19 & 20.’
Become indispensable by exploring untouched areas, and connecting with senior leaders from the likes of Capital One, Netflix, General Electric, Baidu, Google, eBay, Time Inc, MasterCard, Playstation’and many more.’
Check out the agenda here.’
Network with 500+ industry leaders cross-industry, bound by a desire to succeed. Form fruitful relationships and open the door to future investment opportunities or partnerships.’
Speakers include
- Head of Data Science at Microsoft
- Head of Advanced Analytics at Nike
- Global Head of Statistical Programming and Analysis at Roche
- SVP & Chief Technology Officer at Huawei Technologies
- Chief Futurist, Africa at US Department of State’
- Head of Data Science at The Weather Company
- Vice President of Data Analytics at HSBC
- Vice President of Engineering & Product at Fox Sports Interactive
- Manager of Data Science & Engineering at Fitbit’
Futureproof your technical capacities. Review your current models, tools, and predictive capabilities by understanding where to direct investment.’
Avoid costly mistakes’at the initial stage of data collection, and attain the best practices for harvesting data with high potential.’
Join over 500 of the best data & analytics experts in the world by claiming your pass today, use discount code FLOQ10 for 10% off all two-day passes.’
How To Register
You can register online today.’
For more information and group rates, contact Jordan Charalampous at jc@theiegroup.com or (+1 415 614 4191)’
Themes for Discussion?
- Data Science – Machine Learning, Artificial Intelligence?
- Data Governance – Business Intelligence, Data Security?
- Predictive Modeling – Marketing, Consumer Intelligence?
- Data Strategy – Data Culture, Data Products
