The Analytic Executive
Quarterly Breakfast Series

Session 2

Thursday, June 22, 2017
8:00 am - 10:30 am

This seminar series is an event designed specifically for data driven executives, or those hoping to drive their organizations to a high level of analytic competency across all functional areas of the business.

These sessions will be hosted by the Global SAS Best Practices team as they share insights from their experiences in working with other executives in marketing, IT, fraud, analytics/insights, etc. Additionally, a second presentation will be delivered by a SAS partner within academia or consulting to drive further relevance as it applies to each sessional topic.

In this session, we’ll be discussing today’s modern, vibrant analytic ecosystem. Where once there were islands of expertise, open source has helped lower the barriers to access and innovation for analytics practitioners. This, however, has not come without its own set of unique challenges with regards to governance, scalability and support across larger enterprises, which is why SAS has opened key parts of its software to integrate with open source, including R and Python.


Derrick Gray
Director, Audience Measurement Science, Numeris

Derrick Gray is a seasoned senior leader with more than 15 years of advanced analytics and marketing research expertise and is currently Director, Audience Measurement Science at Numeris. The Audience Measurement Science group acts as the Centre of Excellence (CoE) for Advanced Analytics, Data Science and Statistical Research and supports the measurement of Canadian audio and video audiences. Numeris’s audio and video data acts as the transactional currency for the Canadian advertising industry for radio and television ad sales.

Derrick played a key role in the building of the Numeris’ electronic measurement panel - the first multi-media radio/television panel in the world - and has been instrumental in many of Numeris’ statistical and methodological enhancements. Currently he is driving Numeris’s Business Intelligence and Analytics strategy and has been the sponsor of Numeris’s installation SAS Viya, one of the first such installations in Canada.

Derrick holds a Bachelor of Science degree from the University of Toronto in Mathematical Sciences (Statistics), a Master of Science in Statistics from the University of Toronto and is currently a Doctoral Candidate (Doctorate in Business Administration) in Management Information Systems at Athabasca University. His areas of research includes the impact of Big Data on Canadian Audience Information Systems as well as Data-driven decision-making.


Steve Holder
Strategy Executive, Analytic Ecosystems, SAS Canada.

As Strategy Executive, Analytic Ecosystems for SAS Canada Steve Holder is responsible for creating and driving SAS solution strategy in the market.  A key part of this is providing thought leadership for the SAS Analytics, Big Data and Cloud portfolios.  A Canadian analytics evangelist Steve has seen first-hand how the use of analytics and data can help customers solve business problems; make the best decisions possible and unearth new opportunities.   Steve’s passion is making technology make sense for everyone regardless of their technical skillset.

With many years of software industry experience, spanning: management, solutions architecture, presales and sales, Steve brings alignment and execution across SAS’ customers, sales teams, and partners.

Prior to joining SAS in 2014 Steve was Director of solution strategy at SAP and Regional Director at IBM. Steve received his Bachelor of Arts from McMaster University and lives in Toronto with his wife and two daughters.  During his spare time he enjoys traveling, cycling, skiing and spending time outdoors.

Steve tweets at @holdersmTO and can be emailed at

Jesse Luebbert
Global Analytics Practice, SAS Institute

Jesse Luebbert helps customers and prospects understand how SAS advanced analytics capabilities can be applied to their business challenges. In his current role, he marries his understanding of open and SAS technologies to ensure customers to realize the full benefit and impact of their investments in analytics.

Prior to joining SAS, Jesse was employed in the healthcare sector. He holds a BS in mathematics from Abilene Christian University and a master’s in business analytics from Southern Methodist University.

Sasha Pyshkov
Data Operations & Analytics, Sonnet Insurance

Sasha is an open source evangelist with over 14 years of leading agile analytics projects that have a strong emphasis on marketing, customer response and online fraud modeling. In his current role, he’s fostering a culture of data collection, mining and modeling that will enable and imbed AI applications across Sonnet’s business processes and applications.

Always hungry for knowledge, Sasha holds two masters degrees in IT and Analytics, is an active participant in applied research at Queen’s University, and toys with enterprise AI architectures.

In his spare time, he enjoys training recurrent neural networks and kite surfing.

Shak Parran
Partner, Strategic Analytics & Modelling
, Deloitte

Shak Parran is a partner in the Strategic Analytics and Modelling team at Deloitte with over 20 years of experience. Shak is the leader of Deloitte’s public sector, health care and life science analytics team. Prior to joining Deloitte, Shak led the advanced analytics team at a big four consulting firm and founded a successful engineering startup.

As a leader in the Advanced Analytics team, Shak is recognized as the firms’ leading expert in delivering predictive analytics, optimization, analytics strategy and modelling projects across transportation, financial services, CPG, forestry, insurance, health care, utilities and retail industries.

Richard Nestor
AVP Enterprise Advanced Analytics, TD Bank


The St. Andrew’s Club

150 King St. W., 27th Floor 

Additional Resources


Webinar: Taking R and Python from Good to Great with SAS

The SAS Analytics platform is the industry-recognized leader and embraces all major coding languages, methods and application standards for analytics. Our goal is continual innovation in response to customer need.

That’s why SAS has opened up key parts of its software to integrate with R and Python. R and Python are solid programming languages and can bring together data scientists of varied backgrounds and experience to solve complex problems in new ways. But they often lack the scalability, governance and support needed for statistical analysis across your organization.

SAS takes these good languages and makes them great. Your developers can use the languages they know but also have the ability to scale results, put analytical models into action, and meet internal and external regulatory requirements.

View here

An Overview of SAS Viya

SAS Viya is an open, cloud-ready, in-memory architecture that delivers everything you need for fast, accurate analytical results – all of the time. With its fluid, scalable and fault-tolerant processing environment, this resilient architecture addresses the complex analytical chal­lenges of today with the ability to effortlessly scale into the future. SAS Viya provides:

  • A modern, cloud-ready analytics architecture from the analytics market leader.
  •  A single, open and governed analytics environment with a standardized code base that can incorporate both SAS and other programming languages.
  • A uniquely comprehensive and scalable platform for both public and private cloud implementations.

Read here

White Paper: SAS in the Open Ecosystem

Successful organizations recognize that analytics and the models they produce are essential corporate assets that deliver answers to production systems and create channels for improved customer relationships, efficient operations, increased revenues and reduced risks.  

Today, open source is front and center in the software space, including for analytics and data. In this changing landscape, many organizations have realized that they can meet both internal and external stakeholder requirements by finding the right balance of SAS Analytics and Open Source. 

Why? Because SAS embraces and augments the capabilities of open source as part of an analytics ecosystem. The addition of SAS increases productivity, streamlines deployment and allows customers to scale their enterprise analytic platform.

Read here

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Please contact Andrew Bowden


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