Hyatt Regency,
Toronto, ON

Tuesday March 5th &
Wednesday March 6th 2019

2019 Agenda

March 5, 2019
  • 7:45 AM
    Registration and Breakfast
  • 8:45 AM
    Opening Comments from the Chair
    Alyson Gausby
    Head of Research, Twitter Canada
  • 9:00 AM 
    Keynote: Interac
    Embrace Blockchain to Create a Strategic Competitive Advantage
    Oscar Roque
    AVP, Mobile Products & Platform, Interac
  • 9:45 AM
    Industry Expert: Environics Analytics
    Supercharge Your Customer Insights with Mobile Analytics
    Paul Tyndall
    Vice President, Strategic Projects, Environics Analytics

    Location data is complex and can be overwhelming. How can you effectively leverage this privacy-compliant location data to enhance your customer insights? In this session we’ll share several use cases to demonstrate how organizations are applying mobile analytics to answer key business questions. These applications will highlight:

                The unique characteristics of mobile analytics that make it a highly valuable and exciting resource for generating consumer insights—whether you have customer data or not

                How mobile analytics can help retailers, shopping centres, municipalities and others better understand their consumers without the need for implementing costly loyalty programs

                New techniques to gain insights on the competition and how their customers differ from your own

  • 10:15 AM
    Morning Break
  • Track A
    • 10:45 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.

    • 11:30 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
    • 10:45 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
        techniques
      • Overcoming the challenges organizations face is developing and implementing these solutions

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

    • 11:30 AM
      Industry Expert: Informatica
      Employ Predictive Maintenance with Big Data to Avoid Costly Downtime
      Josh Alpern
      VP, Domain Expert Group, Informatica
  • 12:00 PM
    Networking Lunch
  • 1:00 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.

  • 1:45 PM
    City of Brampton’s Dashtopia
    Gustavo Espinosa
    Business Intelligence, Integration, Master Data Management and Quality, Team Leader/Project Manager, City of Brampton

    The City of Brampton has build 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 enrollment, etc.

    By using leading edge tools and systems, the City has been able to deploy an impressive cloud based information hub allowing to rapidly consolidate applications and data and build dashboards and analytics with more agility and flexibility. We collect, clean, match and merge data from over 20 difference sources and persist them into Enterprise Data Warehouse and Master Data Management.

    Solutions includes:

    • 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.

  • 2:15 PM
    Case Study: Twitter
    The Evolution of Service 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.

  • Track A
    • 2:45 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
    • 2:45 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 are disrupting the way we do business and implementations are exploding as we race to reap the benefits. Leapfrog over the challenges of deploying AI to experience 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
  • 3:15 PM
    Afternoon Break
  • 3:45 PM
    Industry Expert: IBM
    Unlock the value of your data in new ways and accelerate your journey to AI
    Deborah Leff
    Director Sales Strategy & Innovation, IBM Cloud Private & IBM Cloud Private for Data Global Leader, IBM Data and AI

    Every organization's 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. Deborah will share new ways to unlock the value of your data and accelerate your journey to AI.

  • 4:15 PM
    Keynote: Privacy by Design
    Lead With Privacy by Design and Gain a Competitive Advantage
    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.

  • 4:45 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
    Mark Sibthorpe
    Publisher, BankNews
  • 8:30 AM
    Keynote
    Laying the Foundation for a Successful Enterprise AI/Machine Learning Strategy
    Lovell Hodge
    Vice President, Data and Adaptive Intelligence, Munich Re

    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
    Avoiding Anti-patterns in Deep Learning Workflows at Scale
    Mike Bloom
    Corporate Advisory Engineer, Dell EMC

    Mike explores the requirements for artificial neural networks, including traditional Convolution Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Antagonistic Neural Networks (GANs), factors that limit scalability at the host, network and filesystem layers and provides best practices for circumventing limitations and potentially accelerating training and scaling inference predictively.

  • 9:30 AM
    Panel
    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.

  • 11:15 AM
    CASE STUDY: WESTJET
    Conversational AI in the Travel industry
    Tania Hoque
    Manager, Mobile Strategy and Emerging Technologies, WestJet

    How are you leveraging chatbots to ease customer interaction, save on resources, and when is human interaction crucial?

  • 11:45 AM
    Networking Lunch
  • 1:15 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.

  • 1:45 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.

  • 2:15 PM
    CASE STUDY: SHOPPERS DRUG MART
    Teach Machines to Learn for Better AI
    Pramod Dogra
    Senior Manager Advanced Analytics, Shoppers Drug Mart
  • 2:45 PM
    End-of-Day Networking Break
  • 3:15 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
    Ira Kaplan
    Product Manager, Data Science, Natural Language Processing
    ,

    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.