Laurie Miles is a Global Director of Cloud Analytics, providing analytical advice and thought leadership globally across all industry verticals. He brings over 25 years of real-world analytics experience to the role. After joining SAS in 1996, Laurie was a consultant delivering analysis focussed projects to organisations from a variety of industry sectors including financial services, telecommunications, retail and utilities. He became SAS UK’s Head of Retail Banking Technology in 2000. Laurie was later appointed Head of Analytics for SAS UK & Ireland in 2008, working with some of the UK’s largest organisations providing strategic advice and forming industry best practice. In this role Laurie also pioneered the development of the SAS Analytics-as-a-Service solution, “SAS Results”. In January 2015 was appointed to lead this globally as part of the SAS Cloud Analytics proposition. Laurie holds a BSc in Econometrics, an MSc in Game Theory and a PhD in Number Theory.
Mathematics and artificial intelligence (AI) are natural partners. I can only apologise to anyone who hated maths at school for this statement, but to my mind, it’s impossible to engage with AI without understanding some maths. One commentator summed it up: “A person working in the field of AI who
In seinem Buch „Competing on Analytics“ benennt Tom Davenport die Analytik als Grundlage nachhaltiger Wettbewerbsvorteile. Der Grund dafür ist der prädiktive Ansatz. Heutzutage ist es nicht mehr möglich, ein Unternehmen alleine mit Blick in den Rückspiegel zum Erfolg zu führen. Und Analytik erlaubt den dringend erforderlichen Blick in die Zukunft.
You could argue that it’s misguided for someone like me to say data science doesn't have to be difficult. After all, I’ve been in the industry for many years and should have a few tricks up my sleeve for dealing with data. But with the latest data visualisation technology –
If I were to believe the feedback I get, statisticians are among the most difficult people to work with. What’s more, they’re the only group that should be allowed to work in data analytics. It sounds harsh, but this may explain why big data projects continually fail. Businesses need statisticians who are both
Well OK, so there is an "i" in science, but being a data scientist is certainly not a lonesome job. Engagement with other team members is essential with data analytics work, so you never really work in isolation. Without the rest of the team, we would fail to ask all
As the age old idiom goes, the early bird gets the worm and the early adopter gets the break. New technologies give clear advantages to those organisations that figure out before their early-adopting competitors how to use them effectively, an advantage that recedes as others catch up, and the technology
In many ways it’s open season for open data; open data is one of those phrases we hear a lot but it’s not always appreciated as having value. The fact that it’s openly available is seen by some as proof that there’s no value in the data – unlike, for
Having worked in analytics for over 25 years, I’ve never really felt part of the ‘cool gang’. However that’s changing and all of a sudden, at long last, it is "chic to be geek!" Research published by SAS UK and the Tech Partnership reveals that from 2013 to 2020, the
I’m sure, like me, you've been annoyed at being stuck in a traffic jam in a city centre somewhere, or been frustrated at your kids leaving lights on, or annoyed with the heating coming on when the weather’s warmed up and you've not got round to adjusting the thermostat. Now,
