I was delighted to attend and present at SAS Forum UK 2017 in Birmingham yesterday. The event started with a vision of an IOT and analytics enabled future spread across a 15 metre wide screen and spanned two days full of talks, demos, discussions, competitions, awards, and pick ‘n mix!

One thing that stood out for me was the slightly strange place in which machine learning sat at the event. There was huge enthusiasm amongst delegates for information about machine learning and how it is being applied in industry. Talks on the subject were packed – my own talk, “All Models are Wrong But Some Are Useful: 6 Lessons for Predictive Analytics”, on how to apply machine learning techniques effectively to build predictive analytics solutions had to be run twice because the original room was not big enough to hold all of the people who wanted to attend – and there was great interest in machine learning training. There were strange moments, though, when delegates were asking SAS staff what new features in SAS software were going to provide support for this new field.  SAS is a leader in the provision of machine learning software (see Gartner, Forbes, etc) and has been for decades. Before machine learning talks and conferences were quite so packed and machine learning researchers were featuring in perfume ads ( http://bit.ly/2xBpJVp ), SAS was providing great tools like Enterprise Miner to help people build and deploy predictive models based on cutting-edge machine learning techniques. They find themselves now in the slightly strange position of having to reintroduce these tools and techniques to the latest (very welcome) wave of converts to machine learning – meet the new SAS, same as the old SAS!

On the subject of new SAS, there were lots of interesting new developments presented at SAS Forum. SAS is continuing to do all kinds of interesting things to modernise their software offerings including integration with open source languages and tools, cloud-based offerings, in-memory databases, and the broad adoption of visual analytics through their Viya toolset (https://www.sas.com/en_us/software/viya.html). If you know ‘old SAS’ or are completely new to SAS it worth having look at what new SAS has to offer.

If you are interested in learning about how you can apply machine leaning techniques in SAS please join us for our new course Fundamentals Of Machine Learning For Predictive Data Analytics Using SAS. Book your place at: https://theanalyticsstore.ie/fundamentals-of-machine-learning-for-predictive-data-analytics-using-sas/

The Team (Nina, Aoife, Aja and Brian) at SAS Forum UK