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.


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