Every year, the SAS Global Forum conference educates and entertains 5,000 data scientists, statisticians, data engineers, strategists and analysts. Knowledge and networking are the objectives across the four-day conference and they were exceeding accomplished again this year.
I’ve been to these conferences for 20 years and have seen SAS change and grow in their product line and capabilities. AI was the focus of this event. SAS has always been a leader in analytics with a full platform to support and advanced analytics to provide the insights. They have had Machine Learning and aspects of AI in their platform for many years. Still each year they expand those analytical capabilities, for example, spending 26 percent of their $3.24 billion revenue in 2017 on research in AI, IoT, data management and analytics software. It was exciting to see the many implementations in such a great conference chaired by MaryAnne DePesquo.
SAS’ Partners are an important aspect of their ecosystem. Before the conference partners from across the U.S. and around the world learned about the new products and capabilities and improvements to the partner relationship. Partner education is important to SAS and we’ve benefited from the many hands-on learning opportunities they offer.
One of the programs that I particularly like is the Managed Analytics Service Provider, or MASP, program. Most clients want strong, valid results at a good price. If they get that, then they often don’t care how it happened. As we learned from Heath Clayton, this Results-as-a-Service style program allows us to create a product for our customers that does exactly that. An easy-to-use, easily repeatable service gives them the results they need without having to worry about the details.
As a SAS Silver Partner, Experis sponsored the conference and had a booth in The Quad. The Quad is an important part of the conference providing education, both group and one-on-one, and networking among the 5,000 conference attendees. Our booth focused on our Data Science as a Service and our Life Science Analytics products. As people came around to pick up our tchotchkes and see who we were, we got to know many of them, as well. They were all types from all walks of life: students, programmers, seasoned SAS users, modelers, data engineers, data scientists; everyone in the analytics lifecycle was there. We took the time to learn their stories, challenges and needs and it gives us a greater capability to create the products they need.
Besides these networking opportunities, I got to meet data scientists in many settings. First, was hosting the Lunchtime Chat where we discussed Creating an Analytics Culture. Even though the excitement around Data Science and Machine Learning is high there are still many competing priorities within an organization, not the least of which is inertia and busy-ness. Getting people to change behavior or add what seems to be more work to their jobs is difficult, even if it helps them in the long run. Our group of new and experienced professionals shared strategies for increasing the awareness of, the desire for, and the ability to provide insightful analytics. Education, user groups, and case studies were all discussed as we learned from each other over lunch.
The second opportunity was to mentor young professionals on Tuesday. Two AutoZone data scientists were very curious about Viya and the future of SAS. It was an exciting conversation about the integration of open source analytics with SAS and the ability of SAS to bring analytics to the enterprise scale.
Sessions and Learning Opportunities
I gave two presentations, including an Invited Panel titled, The Economy of Data Science. Two experienced Data Scientists, Bruce Bedford and Mike Dessauer, joined me to talk about making data science profitable; measuring and convincing management of the ROI; leveraging other culture characteristics to enhance the adoption of data science; the relationship of data science to other hot trends such as robotics, augmented and virtual reality, and cybersecurity; and techniques to overcome the data scientist shortage.
We also had some great questions from the audience about “When is good good enough?”, “How can university programs improve a student’s development?”, “How do you define data scientist?”, “How do jobs such as Data Engineers and Machine Learning modelers relate to data scientist?”, “How can data scientists become entrepreneurs?”, “How to use Customer Lifetime Value to measure the value of Data Science work?”, “How can we engage with high school students?”, “How big should your group be before you decentralize your data scientists?”, “How do you foster collaboration among potentially siloed data scientist teams?” and “How can we create data scientist opportunities for people with neurological disabilities?” The video of the panel can be found on the SAS Global Forum website and scroll down on the right to “Experis: The Economy of Data Science.”
Finally, the networking doesn’t end in The Quad and sessions. We had a great time at Gilley’s riding the mechanical bull; listening to what I thought was Slam Poetry but turned out to be a Trivia Challenge; and enjoying four great bands.
I can’t wait to see what happens next year in Washington, D.C.