laptop with clouds

Enabling better decisions faster
with analytics in the cloud

Provisioning analytics environments can include designing and delivering software, infrastructure and services – or simply signing up, logging in and getting to work. Join this panel to explore lessons for enterprise analytics managers from the analytics environment built for the recent SAS Hackathon.

#SASchat

Discussion triggers

  1. What were the user experience and design priorities for hack sandbox provisioning developed?
  2. How were other considerations assessed?
  3. Why was self-service deemed important?
  4. Where was automated provisioning most appropriate?
  5. What lessons from the hackathon can architects apply internally in enterprise production environments?

Further reading

8 Best practices for moving analytics to the cloud

BookmarkSubscribe Create an analytics platform strategy in 5 stages

Publishing your model into a container

Running Python models in SAS using Kubernetes volumes and Azure Files storage

Using Amazon’s Athena as a data extraction interface to S3