DIY versus designer approaches to deploying data center infrastructure for machine learning and analytics
Cory Minton and Colm Moynihan explain how to choose the right deployment model for on-premises infrastructure to reduce risk, reduce costs, and be more nimble.
| Talk Title | DIY versus designer approaches to deploying data center infrastructure for machine learning and analytics |
| Speakers | Cory Minton (Dell EMC), Colm Moynihan (Cloudera) |
| Conference | Strata Data Conference |
| Conf Tag | Make Data Work |
| Location | New York, New York |
| Date | September 11-13, 2018 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Custom or commodity? Specialization or standardization? Control or convenience? These aren’t hypothetical questions for enterprises choosing a primary deployment model for your infrastructure. Join Cory Minton and Colm Moynihan for an unbiased look at the critical considerations for building or buying a hardware environment that meets your requirements for machine learning and analytics. They compare bare metal servers, appliances, private clouds, public cloud infrastructure as a service and platforms as a service, and reference architecture options as they explain how to optimize IT’s operational costs and effort while meeting the needs of various line of business stakeholders.
