Hyatt Regency,
Toronto, ON

Tuesday March 5th &
Wednesday March 6th 2019

2019 Agenda

March 5, 2019
  • 7:15 AM
    Registration and Breakfast
  • 8:15 AM
    Opening Comments from the Chair
  • 8:30 AM
    Keynote: Interac
    Embrace Blockchain to Create a Strategic Competitive Advantage
    Oscar Roque
    AVP, Mobile Products & Platform, Interac
  • 9:15 AM
    CDO Panel
    Source Insights on the Latest Big Data Trends
    Pamela Snively
    Vice President, Chief Data & Trust Officer, Telus
    John Walsh
    Chief Data Officer, Chief Delivery and Results Officer, Environment and Climate Change Canada
    Peter Papadakos
    Decision Support & Analytics, Health Information Services, and Chief Privacy Officer, Quinte Health Care

    Big data is a fast-moving field with constant innovations and new opportunities. Stay on top of the latest trends to help your organization monetize big data. Gain insights to:

    • Explore new and emerging trends
    • Understand the future potential of big data
    • Monetize your data

    Source key insights from c-suite data leaders to transform your organization

  • 10:00 AM
    Industry Expert: Environics Analytics
    Session Details Coming Soon
  • 10:30 AM
    Morning Break
  • Track A
    • 11:00 AM
      Case Study: Norton Rose Fulbright
      Understand the Legal Landscape to Make the Most of AI While Staying on the Right Side of Regulations
      Anthony de Fazekas
      Partner, Lawyer, Patent Agent, Head of Technology & Innovation, Norton Rose Fulbright

      The legal landscape in a fast-moving field like AI can be unclear. Get the clarity you need to make business decisions. Gain insights to:

      • Understand the relevance of copyright laws to AI/ML; and the protectability of AI/ML
      • Comply with privacy regulations
      • Anticipate potential legislative changes

      Gain an understanding of the legal landscape for AI in Canada to inform business decisions.

    • 11:45 AM
      Industry Expert: Alithya
      Machine Learning for the Financial Industry
      Jim Picha
      VP of Consulting Services for the Financial Sector, Alithya
      Naresh Tejpal
      Senior Director, Capital Markets Compliance, CIBC

      Capital Markets Trade Surveillance relies mainly on human judgment and manual processes to identify potential fraudulent activities. To overcome these challenges and inefficiencies, Alithya proposed CIBC adopt a machine learning (ML) approach for their trade surveillance. In 2018, CIBC’s Advanced Trade Surveillance system was completed, and representatives from both Alithya and CIBC will share:

      • Challenges faced by trading compliance
      • Key ML design decisions
      • Results
      • Lessons learned in delivering a machine learning project

      The manual processes within the financial industry will be transformed by the power of artificial intelligence.
      Learn about the challenges and benefits of adopting machine learning to augment your manual processes.

    Track B
    • 11:00 AM
      Case study: Region of Peel
      Use Artificial Intelligence and Machine Learning to Develop Autonomous Business Solutions
      Faraz Zaidi
      Advisor Health Analytics, Health Services, Region of Peel

      Recent advances in AI and ML have led to the development of innovative solutions and capabilities for a variety of sectors such as Sales and Marketing, Financial Services, Automotive Industry and Healthcare Providers. Common goals and objectives pertaining to these domains are, respectively, ‘I want to make more money,’ ‘I want to have more clients,’ I want to develop a self-driving car,’ ‘I want to improve the health of my patients.’ Achieve these goals by:

      • Modeling these objectives as qualitative problems
      • Using advanced analytical and computational methods to develop solutions using state-of-the-art algorithms and
      • Overcoming the challenges organizations face is developing and implementing these solutions

      Create autonomous business solutions with the support of AI and ML.

    • 11:45 AM
      Industry Expert: Informatica
      Employ Predictive Maintenance with Big Data to Avoid Costly Downtime
      Josh Alpern
      VP, Domain Expert Group, Informatica
  • 12:15 PM
    Networking Lunch
  • 1:30 PM
    Industry Expert: Information Builders
    Big Data Infrastructure to Unlock the Power of Machine Learning and AI
    John Ramoutsakis
    Vice President, Canada, Information Builders (Canada) Inc
    Dr. Pascal Tyrrell PhD
    Director of Data Science, Department of Medical Imaging, University of Toronto
    Professor, Medical Imaging & Statistical Sciences, University of Toronto

    Artificial intelligence (AI) has received a lot of attention over the years. Most AI schemes depend on the availability of big data. However, using AI algorithms on large datasets requires a good understanding of their requirements and limitations. In this talk, we will explore the potentials and challenges of AI technologies in order to attain a realistic grasp on how we could employ them for real problems efficiently.

  • 2:15 PM
    Put Analytics in the Hands of Employees to Create a Data-Driven Organization
    Jason Garay
    Vice President, Analytics and Informatics, Cancer Care Ontario
    Christian Rodericks
    Director Analytics and Architecture, Cara Operations
    Saad Rais
    Lead Data Scientist, Ontario Ministry of Health and Long-Term Care
    Michael Morris
    Director, Sales Analytics and Incentive Programmes, Global Furniture Group

    Data can provide essential insights to the wider business when employees have access to them. Empower employees by giving them access to
    data and analytics. Develop a plan to:

      • Train and educate the wider business in the use of data and analytics
      • Provide dashboards and simplified access to data and analytics
      • Create a culture that embraces data

    Empower employees with data to drive your organization.

  • Track A
    • 3:00 PM
      Industry Expert: Schulich Executive Education Centre
      Digital Transformation in Retail Banking and the Role of Digital Service Development
      Murat Kristal PhD
      Program Director and Director, Master of Business Analytics Program, Schulich School of Business

      Today, the financial industry is undergoing tremendous changes due to the rapid advancement of technology. Numerous financial innovations are enabled by emerging technologies like Artificial Intelligence, Blockchain, cloud-computing and etc. Digital finance is considered to be the next-generation finance ecosystem, and digital transformation has become a top priority. For financial institutions, digital transformation involves not only digitizing existing services or products but also developing relevant capabilities to generate new digital services. To measure company’s efforts in generating digital services options and examine the impact of digital transformation on service performance, we are launching a global survey, entitled Innovation in Digital Services. This survey will explore the extent to which retail banks are investing in, developing and delivering digital services over time, and how well they are performing against customer expectations. Trending topics, such as digital service development, digital culture, digital trust and confidence, FinTech competition and collaboration, and etc., will be covered. Results from this survey are expected to inform banking executives on key drivers and best practices for undertaking in and delivering digital transformation and help retail banks to better seize digital moments

    Track B
    • 3:00 PM
      Industry Expert: Alteryx
      How Self-Service Analytics Delivers Machine Learning and Artificial Intelligence Insights
      Joe Cooper
      Canadian Country Manager, Alteryx

      Artificial Intelligence and Machine Learning will disrupt the way we do business, but just 4% of CIOs have implemented AI to date. Leapfrog over the challenges of deploying AI and reap benefits like new growth, optimized business models, and increased customer engagement.

      • Understand and overcome challenges to deploying AI/ML
      • Learn how professionals without a data science background can use AI
      • Discover how to overcome the three biggest challenges in enterprise analytics
      • Get inspired with stories from Home Depot and Western Union
  • 3:30 PM
    Afternoon Break
  • 4:00 PM
    Industry Expert: IBM
    Unlock the value of your data in new ways and accelerate your journey to AI
    Alyse Daghelian
    Vice President, Global Analytics Sales, IBM

    Every organizations journey to AI will be different, however, key principles still exist. Collecting your data to make it simple and accessible; organizing your data so that it’s built on a trusted foundation; analyzing your data to provide the insights on demand and modernizing your data to make it ready for the Cloud and AI remains unchanged. Hear use cases on how data science, machine learning and other open source tools have been leveraged to build winning data, analytics and AI strategies. Alyse will share new ways to unlock the value of your data and accelerate your journey to AI.

  • 4:30 PM
    Keynote: Privacy by Design
    Leverage Privacy by Design to Achieve your Business Needs Through Big Data Without Compromising Privacy
    Dr. Ann Cavoukian
    Distinguished Expert-in-Residence, Privacy by Design Centre of Excellence, Ryerson University

    Organizations today are looking into how consumer, social media, and web traffic data can help drive business. However, companies need to be aware of the backlash involved and the privacy concerns that are brought to the forefront of big data discussions:

    • Overcome privacy challenges with new data sources
    • Manage customer data privacy expectations
    • Promote data privacy best practices

    Be proactive: create big privacy for big data.

  • 5:00 PM
    Conference Adjourns to Day Two
  • 5:05 PM
    Cocktail Reception
March 5, 2019
March 6, 2019
  • 7:45 AM
    Registration and Breakfast
  • 8:15 AM
    Opening Comment from the Chair
  • 8:30 AM
    Keynote: TD Bank Group
    Laying the Foundation for a Successful Enterprise AI/Machine Learning Strategy
    Lovell Hodge
    Vice President, North American Fraud Analytics, Financial Crimes & Fraud Management Group, TD Bank Group

    Enterprise-wide AI programs are no small investment. Ensure meaningful returns on this investment with a strategy to support AI and machine learning. Develop a plan to:

    • Assess your AI/ML capabilities
    • Determine the objectives of AI/ML for your organization
    • Track the success of your program

    Make your AI and machine learning program a success with a strategic plan.

  • 9:00 AM
    Industry Expert: Dell EMC
    Dell EMC

    Session details coming soon.

  • 9:30 AM
    Competing in the War for Big Data Talent
    Brian Hu
    Head of Data , Index Exchange
    Peter Husar
    Vice President, Analytics Strategy & Planning Enterprise Data and Analytics, TD Bank Group
    Aliza Lakhani
    CEO, Northeastern University Toronto
    Houtsin Diep
    Analytics Manager, Digital, McDonald's Restaurants of Canada Limited

    The demand for qualified big data experts has outpaced the labour supply. Position yourself to compete for the best and brightest in the field. Create a plan to:

    • Identify and attract top talent
    • Work with universities to create a supply of qualified big data experts
    • Compete for talent against Silicon Valley and other markets

    Develop a plan to attract and retain top big data talent.

  • 10:15 AM
    Morning Break
  • 10:45 AM
    Industry Expert: SAS
    Building an AI application using Machine Learning
    Cindy Zhong
    Sr. Data Scientist, SAS
    Lorne Rothman
    Principal Data Sciences Specialist, SAS

    Artificial Intelligence is the science of training systems to emulate human specific tasks through learning and automation. An AI application serves to automate and accelerate work that would otherwise take human resources and time. Machine Learning provides the intelligence that powers the AI application. We present an example of an AI app: a website where applicants can simply add house location and attributes to estimate home value for a mortgage application. A machine-driven estimate and decision are returned instantly. We will uncover the process of building this app--from Data Preparation and Machine Learning to Deployment.

  • Track A
    • 11:15 AM
      Case Study: Twitter
      The Evolution of Science When your Consumer Never Sleeps
      Alyson Gausby
      Head of Research, Twitter Canada

      Each and every day, millions of people on Twitter reach out to brands looking for help. The opportunity to answer questions, engage in conversations, and respond to concerns in real time, 24/7 demands a new approach to customer care. Consumers insist on speed, transparency, and accuracy but that’s not easy at scale. Today, only 40% of Canadians say they see good customer service on social media, yet nearly 2/3 say the service they receive impacts their future purchase behaviour. This session will share new research insights and tips and tricks for how to improve engagement with your customers, including a consumer-focused deep dive into the world of chatbots - how they can help and what impact they have on customer care.

    • 12:00 PM
      Industry Expert
      Monetize Big Data to Improve your Bottom Line

      The true value of big data is found when it is applied to drive business improvements and increase revenues. Unleash the potential of big data to improve your profits. Source original strategies to:

      • Optimize your sales and marketing strategy
      • Increase customer loyalty
      • Move from descriptive analytics towards prescriptive revenue generation strategies

      Convert your data into profitable business intelligence.

    Track B
    • 11:15 AM
      How AI Is Changing How We Travel
      Tania Hoque
      Manager, Mobile Strategy and Emerging Technologies, WestJet
    • 12:00 PM
      Industry Expert
      Create a Roadmap to Ensure Enterprise-Wide Success of Big Data and Analytics

      Implementing big data and analytics is a high-level strategic undertaking. Take an enterprise-wide approach as you develop a big data and analytics strategy. Walk away with a proven plan to:

      • Establish your strategic vision
      • Gathering business requirements and data analysis needs
      • Defining an information architecture

      Develop your competitive advantage with a well thought-out big data roadmap.

  • 12:30 PM
    Networking Lunch
  • Track A
    • 1:30 PM
      Industry Expert
      Get Beyond the Hype of AI and Machine Learning to Make a Real Impact on your Business

      There’s a lot of hype surrounding AI. Get beyond the hype and find out what practical effects AI can have on your organization today. Gain expert insights to:

      • Identify AI applications that you can implement now
      • Manage your expectations for AI
      • Create a plan to develop your AI capabilities

      Identify real applications that AI can have on your organization today and in the near future.

    • 2:00 PM
      Case Study: Beth Israel Deaconess Medical Center
      Building a Data Platform for Better Insights
      Ayad Shammout
      Director of Data Management & Analytics, Beth Israel Deaconess Medical Center

      There is a growing demand for better Healthcare IT and Analytics to drive better patient care services and business decisions. Analytics require managed data platform as a foundation for Business Intelligence, Data Mining and Advanced Analytics with modern data visualization. Data Management is an essential process that provides data governance, data modeling, and data visualizations.
      In this session, I will share how we are developing an Enterprise Data Management Platform and build a better innovative analytical program to introduce new technologies that help in solving complex business issues.

    • 2:45 PM
      Case Study: Ontario Telemedicine Network
      Leverage Academic Partners to Advance your Big Data and Analytics Program
      Jordan Himel
      Head, New Venture Development, Ontario Telemedicine Network

      Take advantage of Canada’s strong network of data researchers to drive real business results. Source best practices to:

      • Develop partnerships with academics
      • Support commercial activities with the help of academic partners
      • Develop real-world applications for data research

      Partner with the academic world to drive business results.

    Track B
    • 1:30 PM
      Industry Expert
      Improve Natural Language Processing to Develop Better Chatbots

      Chatbots have the ability to improve customer experience and free up employees, but only if they are highly functional. Improve the way your chatbots function with better NLP. Gain insights to:

      • Develop better AI-based long conversations
      • Improve open domain conversations
      • Create AI with a consistent personality

      Develop better chatbots with the aid of improved natural language processing.

    • 2:00 PM
      Case Study: City of Brampton
      Deploy a Dashboard to Drive Results

      The City of Brampton has built and deployed several analytical solutions including interactive dashboards, data warehouse and master data. These solutions are bringing numerous benefits to Brampton’s constituents and staff such as more reliable public transportation, ridership increase, reduction in complains, faster service request resolution, faster response to complaints, increase in recreation programs enrolment, etc.
      Solutions include:

      • Transit
      • Enforcement
      • Recreation
      • Fire
      • PMO
      • Service Brampton

      This session will show the journey to Brampton’s information and analytics depicting how it was done, what was done, who did it, which solutions were delivered and which tools were used.

    • 2:45 PM
      Case Study: BankNews
      Use Cloud to Prototype and Deploy Big Data Solutions
      Mark Sibthorpe
      Publisher, BankNews

      Big data projects don’t need to be expensive. Explore cloud options to develop big data solutions that can scale.
      Source insights to:

      • Prototype big data solutions
      • Builds partnerships with subject matter experts
      • Deploy and assess your tools

      Use cloud tools as a cost effective way to test environments and deploy sophisticated big-data tools.

  • 3:15 PM
    Afternoon Break
  • 3:45 PM
    Case Study: Law Society of British Columbia
    Proactive Regulation Powered by Data Analytics and Machine Learning
    Thomas Kampioni
    Manager, Information Services, The Law Society of British Columbia

    Many non-profit regulatory bodies face a pressure of being an effective and efficient regulator but having limited funding. In order to achieve its organizational objectives and meet KPMs, organizations must take advantage of collected data and use machine learning to identify trends, patterns and certain indicators that are crucial in making informed decisions about the future. Take back to your office strategies to:

    • Introduce affordable machine learning solution to your organization
    • Use predictive analytics to optimize the usage of your resources and effectiveness of your programs and processes
    • Tell the story through data visualization

    Take away practical ideas that you can apply to your organization on how to introduce proactive approach toward regulation and foster a data-driven culture.

  • 4:30 PM
    Teach Machines to Learn for Better AI
    Pramod Dogra
    Senior Manager Advanced Analytics, Shoppers Drug Mart
  • 4:30 PM
    Case Study: Cara Operations
    Use Data Visualization to Better Communicate Information

    Data, even when analyzed, is valueless, unless it can be understood and used by business leaders and frontline workers. Employ visualization to improve the way data is communicated so it can be better used across the business. Source practical tips to:

    • Transform complicated data sets into easily understood graphics
    • Use visualization to tell the story of data
    • Uncover insights not apparent in text format

    Improve the way you communicate data through visualization.

  • 5:00 PM
    Conference Adjourns
March 6, 2019
March 7, 2019
  • 9:00 AM - 12:00 PM
    Workshop A
    The ABCs of Preparing Your Data for AI & Machine Learning
    Aditya Sriram
    Data Scientist, Information Builders
    Lisa Scipio
    Product Manager, Information Builders

    Recent breakthroughs in the domain of Artificial Intelligence applications have brought Machine Learning to the forefront of new generations of data analytics. In this workshop, we will present the practice and design trade-offs of building Machine Learning applications for production data and workflow on Big Data platforms.

    Join us as we:

    • discuss business challenges and best-practices to implementing AI & Machine Learning
    • identify use cases that best fit your organization
    • provide a foundation to build and productionize Machine Learning applications.

    Walk away with a preliminary plan to better understand your data and the impact it will have in your Machine Learning use case.

    The event is designed to educate, inform and inspire organizations across all verticals. We look forward to seeing you there!

  • 1:00 PM - 4:00 PM
    Workshop B
    Experience the SAS Platform! Explore the latest Visual Data Mining and Machine Learning capabilities
    Kieran DeFilippis
    SAS Data Scientist, SAS
    Sabrina Mancini
    SAS Data Scientist, SAS

    Users of all skill levels can visually explore data and create analytically driven visualizations while tapping into powerful in-memory technologies for faster computations and deeper discoveries. This easy-to-use, self-service data visualization and analytics software can handle all your data, putting approachable and deep analytics in the hands of all users.

    Facilitated by SAS experts, this 3- hour workshop is designed to teach you to uncover hidden opportunities, identify key relationships and make more precise decisions to drive success.

    In this hands-on workshop, you will learn how to:

    • Go from data to insight with the SAS Platform
    • Data Exploration
    • Investigating the Modeling Data
    • Model Building, Discussion and Assessment
    • Building, Fitting and Comparing Predictive Models Using Pipelines in Model Studio
    • Model Management and Scoring
    • Managing a Champion Model and Scoring
March 7, 2019

Download Brochure - Gain new ideas and practical strategies for implementation

  • This field is for validation purposes and should be left unchanged.