Agenda

February 7, 2018
  • 7:30 AM
    Registration and Breakfast
  • 8:30 AM
    Opening Comments from the Chair
    Bala Gopalakrishnan
    Managing Director, Data Solutions, The Weather Network
  • 8:45 AM
    Keynote: Royal Caribbean International
    Using AI to Personalize your Customers’ Experiences
    Sol Rashidi
    Chief Data & Cognitive Officer, Royal Caribbean International

    Artificial intelligence isn't just a buzzword, it's a reality and it has the ability to drive real business results. Hear how AI can improve your customers' experiences. Create a plan to:

    • Create a data-centric organization
    • Customize your offerings
    • Personalize your customers’ experiences

    Leverage your data using AI to improve the experiences of your customers.

  • 9:30 AM
    Industry Expert
    Employing Machine Learning to Identify Hidden Risks and Opportunities

    Machine learning applies algorithms that learn as they process data. Use this technology to uncover hidden insights that your systems have not been expressly programmed to find. Create a plan to:

    • Mine data to identify investment opportunities and risks
    • Analyze data to create personalized shopping experiences
    • Identify patterns to reveal efficiencies in business processes

    Reveal hidden insights in your data with the power of machine learning.

  • 10:00 AM
    Morning Break
  • 10:30 AM
    Case Study: Cirque du Soleil
    Leverage Customer Analytics and Consumer Insights to Develop a Customer-centric Organization
    Axel Bedikyan
    Director of Business Analytics and Consumer Insights, Cirque du Soleil

    Most companies are sitting on mountains of data, but that data needs to be transformed into meaningful insights. Leverage your data to create a customer-centric organization. Develop a strategy to:

    • Leverage customer analytics
    • Harness consumer insights
    • Drive business value with data

    Better serve your customers by converting data into actionable insights.

  • 11:00 AM
    Industry Expert:
    Session Details Coming Soon
  • 11:30 AM
    5 Minute Room Change Break
  • Technical
    • 11:35 AM
      Case Study: Shoppers Drug Mart
      Predictive vs. Prescriptive Analytics: Choosing the Right tools to Drive Results
      Pramod Dogra
      Senior Manager, Advanced Analytics, Shoppers Drug Mart

      Predictive analytics allow you to identify and exploit opportunities, while prescriptive analytics takes it to the next level: prescribing a range of actions and potential outcomes. Using these analytical tools can help you make better business decisions. Source insights to:

      • Apply decision analysis and optimization, transactional profiling, and predictive modeling
      • Employ prescriptive analytics to select a best course of action
      • Select the right analytics to achieve your goals

      Leverage predictive and prescriptive analytics to make better business decisions.

    • 12:05 PM
      Industry Expert:
      Take the Plunge into Data Lakes for Faster and More Robust Analysis

      Data lakes have the potential to improve access to data and increase the speed of analysis. Explore how your organization can use a data lake to turn data into actionable insight. Source an action plan to:

      • Integrate existing data into data lakes
      • Improve the accessibility of data without the structural limitations of warehouses
      • Address business needs in a timely manner

      Analyze your data quickly and make insights accessible with data lakes.

    Business Use
    • 11:35 AM
      Case Study: DLA Piper
      Gain a Legal Perspective on Big Data
      Kelly Friedman
      Partner, DLA Piper

      Businesses are eager to take advantage of big data, but the legal implications are unclear to many. Understand how your organization can take advantage of big data while staying on the right side of Canadian laws and regulations. Gain insights on:

      • The current legal and regulatory framework to be applied
      • Maintaining privacy and security
      • Moving forward with Big Data projects while managing risks

      Source insights on how Canadian law treats your use of big data.

    • 12:05 PM
      Assessing the ROI of Big Data to Demonstrate Value and Gain Support

      In order to receive support, big data programs must be able to show the value that the core business derives from them. Make the case for your big data program in cold, hard numbers. Take strategies back to your office to:

      • Identify the real costs of analytics programs
      • Discover and assess KPIs
      • Demonstrate the monetization of big data

      Show the costs and benefits of your big data program to develop organizational support.

  • 12:35 PM
    Networking Lunch
  • Technical
    • 1:30 PM
      Panel
      Handling Disparate Data to Make Better Business Decisions
      Pankaj Arora
      VP Business Planning, Analytics and Performance Enablement, TD Bank Group
      Kathryn Todd
      Vice President, Research, Innovation & Analytics, Alberta Health Services
      Houtsin Diep
      Manager, Digital Analytics (Lead), McDonald's Canada

      Most organizations deal with internal and external data from a variety of sources. Overcome these challenges to make the most of your data. Gain insights on how to:

      • Make use of data from various sources
      • Integrate unlike data
      • Handle redundant data

      Use heterogeneous data to better inform business decisions.

    • 2:30 PM
      Industry Expert
      Securing Big Data to Avoid Breaches

      As the size of the data you store increases, so does the potential damage of a breach. Develop a strategy to keep your data out of the hands of cyber attackers. Source best practices to:

      • Develop a secure infrastructure to house data
      • Monitor employee account access to prevent internal breaches
      • Secure applications and hardware to minimize vulnerabilities

      Keep your data out of the hands of cyber attackers with appropriate security measures.

    Business Use
    • 1:30 PM
      Panel
      Communicating Data and Analytics to Inform the Larger Business
      Sylvie Makhzoum
      Vice President Data, Analytics & Insights, TD Insurance
      Christopher Brockbank
      CMO, FIRMA Foreign Exchange
      Matthew Andaloro
      Senior Manager, Revenue Performance and Analytics, Infrastructure Ontario

      Data and analytics can provide essential insights to the wider business, but only if they are understood. Better communicate your data to support business decisions. Develop a plan to:

      • Convey data and analytics to stakeholders who lack an analytics background
      • Employ visualization and storytelling to make data understood
      • Help other departments to better understand data and analytics

      Inform the wider business about data and analytics to provide actionable insights.

    • 2:30 PM
      Industry Expert
      Employing Predictive Maintenance With Big Data to Avoid Costly Downtime

      As we enter the “Internet of Things” era, the increased availability of data allows you to perform maintenance proactively. Embrace predictive maintenance to maintain your productivity and avoid lost revenues. Go back to the office with strategies to:

      • Integrate IoT data sources to improve maintenance decisions
      • Monitor equipment and facilities in real-time to anticipate maintenance needs
      • Establish a maintenance policy based on data to reduce costs

      Reduce your unnecessary downtime with predictive maintenance.

  • 3:00 PM
    Afternoon Break
  • 3:30 PM
    Case Study: brightpeak financial
    How Big Data and Behavioural Science Shape the Future of Marketing
    Mike Milkovich
    Chief Technology Officer, Brightpeak Financial
    Cami Zimmer
    Head of Corporate Communications, Brightpeak Financial

    Spending and saving is a rich area of exploration for big data studies. What’s missing is an exploration of people’s attitudes about spending and saving, as well as their behaviours leading up to those actions. In this session, source insights on:

    • The importance of converging motivation, ability and triggers to change behaviours
    • Examples on how behavioural change is needed to drive outcomes
    • Real case studies on what has worked and what hasn’t

    Source a strategy to leverage big data and behavioural science to drive business results.

  • 4:00 PM
    Industry Expert
    Using Self-service Analytics to Improve Business Leader Decision-making

    Guided, self-service analytics tools put the power of analytics in the hands of business leaders – not just the data scientists. Identify the tools you need to put the power of analytics in the hands of key decision-makers. Develop a plan to:

    • Empower users with agile and intuitive platforms
    • Create a simplified and personalized approach to analytics
    • Create a scalable IT solution to meet business demands

    Maximize your ability to leverage data with self-service analytics.

  • 4:30 PM
    Panel:
    Identifying New Trends and Opportunities to Monetize Big Data
    Dean McKeown
    Associate Director, Administration, Scotiabank Centre for Customer Analytics, Queen's University
    Vicky Marsolais
    Director, Data and Analytics, National Programs and Strategies, CAA (Canadian Automobile Association)
    Christian Rodericks
    Director Analytics & Architecture, Cara Operations

    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

    Turn your data into profits by exploring the latest trends in the field.

  • 5:15 PM
    Conference Adjourns to Day Two
  • 5:20 PM
    Executive Reception
February 7, 2018
February 8, 2018
  • 8:00 AM
    Registration and Breakfast
  • 8:30 AM
    Opening Comment from the Chair
    Bala Gopalakrishnan
    Managing Director, Data Solutions, The Weather Network
  • 8:45 AM
    Keynote: XE.com
    Leveraging Real-time Events in Customer-centrification and Predictive Analytics
    Cecilia Tamez
    Chief Strategy Officer, XE.com
    Jean Louis Verboomen
    Director, Data Science, XE.com

    The drive towards customer-centrification dictates the need for a technological environment that enhances customer relationships and, above all, works to strengthen customer loyalty. Monitor and track your customers' omni-channel interactions in real time to optimize the customer journey. Create a strategy to:

    • Collect and assess real-time data
    • Couple real-time data with historic customer interactions
    • Personalize the marketing experience

    Create a customer-centric organization using predictive analytics.

  • 9:15 AM
    Industry Expert
    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.

  • 9:45 AM
    Panel
    Develop Cross-department Support to Enable your Big Data Projects
    Selwyn Collaço
    Chief Data Officer, TMX Group
    Andrew Brown
    Senior Director, AI and Advanced Analytics Research, CIBC
    Gayle Ramsay
    Vice President, Customer Analytics, BMO Financial Group

    The effectiveness of a big data project depends on the support of the organization as a whole. Work with stakeholders in your organization to ensure your program’s success. Walk away with a plan to:

    • Involve divers programs in your data program
    • Get senior management on board with big data
    • Gain the support of front line workers for data and analytics

    Ensure that your data and analytics programs are supported across the organization.

  • 10:30 AM
    Morning Break
  • Technical
    • 11:00 AM
      Interactive Problem Solving Forum:
      Overcoming Common Issues When Implementing a Big Data Program

      Implementing a big data program in a technically challenging undertaking. Identify common problems and work with your peers to develop solutions based on your collective experience. Work together to develop best practices for the technical side of big data programs. Source strategies to:

      • Transition from legacy systems
      • Manage privacy and security
      • Implement data lakes

      Gather technical insights from big data leaders.

    • 11:30 AM
      Case Study: Scotiabank
      Use Big Data Analysis to Mitigate your Risks
      Nima Safaei
      Associate Director, Network Analytics, Scotiabank Global Banking and Markets

      The forecasted regulations and competition pressures enforce banks to carefully comply with risk factors. Explore how you can employ machine learning and big data methods to extract risky components. Achieve a step-by-step action plan to:

      • Integrate data from different departments into a single network representation.
      • Identify secondary relationships at various levels even in the absence of financial relationship
      • Analyze the microstructure of the Cross-border Payment Network to identify the suspicious components having a potential for risky activities and illicit behaviour.

      Take away experienced insights to help you make the right de-risking and onboarding decisions.

    • 12:15 PM
      Industry Expert
      Develop a Scalable, Agile Framework to Support your Big Data Initiative

      As you build your big data and analytics program, you must be prepared for your needs to change. Develop a program that can adapt as it grows. Source a framework to:

      • Start small and scale your program up
      • Anticipate your needs to prepare for the future
      • Be flexible and adaptable to ensure continued relevance

      Improve your operations and business outcomes through an efficient, scalable and agile platform.

    Business Use
    • 11:00 AM
      Interactive Problem Solving Forum
      Breaking Down Silos to Create an Effective and Efficient Data Program

      An effective big data program requires collaboration across business units. But unfortunately, many organizations are dealing with silos in which knowledge is not shared across units. Gain insights from your peers as you work collaboratively to identify the causes of silos and source best practices for breaking them down. Develop a plan to:

      • Identify causes of silos
      • Improve communication
      • Enhance interdepartmental collaboration

      Make the most of your data with improved data sharing and collaboration.

    • 11:30 AM
      Case Study: Global Furniture Group
      Smoothly Navigate your Path to Bring Business Intelligence to your Organization
      Michael Morris
      Director, Sales Analytics and Incentive Programmes, Global Furniture Group

      Moving a company into Data Analytics is a monumental task. Reduce your anxiety with insights from someone who’s been down this bumpy road. Discover practical tips to:

      • Smoothly navigate your path to bringing business intelligence to your organization
      • Enhance team building to support your vision
      • Distil the promises to help make your software decisions

      Take away a roadmap to help begin your journey to making informed business decisions.

    • 12:15 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.

  • 12:45 PM
    Networking Lunch
  • 2:00 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
    • Gather business requirements and data analysis needs
    • Define an information architecture

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

  • 2:30 PM
    Case Study: Maple Leaf Sports and Entertainment
    Building your Analytics All-Star Team
    Sean O’Brien
    Director of Analytics & Research, Maple Leaf Sports and Entertainment

    The analytics talent race is underway.  Organizations globally are competing for top-tier analytics and data science talent, and acquiring the right people for your organization can seem impossible.  Learn how MLSE has built their data analytics/science practice with a focus on:

    • Recruiting, empowering, and unleashing talent
    • Creating a culture of experimentation and IP generation
    • Generating and measuring business value

    Take away specific and practical solutions for navigating the analytics talent shortage.

  • 3:00 PM
    Case Study: Enterprise Saint John
    Size Matters: How a Small Community is Harnessing the Power of Data to Drive Economic growth
    Janet Scott
    Director, Business and Community Development, Saint John
    Mirko Crevatin
    Program Manager, Enterprise, Saint John

    Many small businesses and organizations struggle to access the resources, knowledge, and infrastructure to capture, collect and analyze data in meaningful ways. Small communities may be in a better position to collaborate to fill these gaps in ways they don’t often realize.

    Learn how to build a data ecosystem that:

    • Engages businesses and organizations of all sizes
    • Builds partnerships with subject matter experts
    • Develops shared data assets and infrastructure
    • Drives innovation

    You will discover how a small Canadian City is building on its industrial and innovative past by harnessing the power of data and partnerships.

  • 3:30 PM
    Afternoon Break
  • 4:00 PM
    Case Study: American Hospital Association
    How to Introduce and Implement a Data Strategy to Improve Decision-making
    Gloria Kupferman
    Chief Data Strategy Officer, American Hospital Association

    Membership organizations have long relied on personal interactions for member engagement while employing consulting firms to perform advocacy analyses. Optimize data and analytics to increase your member value and enhance your ability to influence policy-makers. Gain insights on how to:

    • Harness the power of your own data
    • Create unique user experiences in the digital arena
    • Make better, data-driven decisions

    Take away expert perspectives to inform your own data strategy.

  • 4:30 PM
    Case Study: Blockchain Association of Canada
    Take Advantage of One of the Biggest Technological Revolutions
    Kyle Kemper
    Executive Director, Blockchain Association of Canada

    Blockchain – the technology behind bitcoin – is getting a lot of attention in the world of financial services, but its potential extends to virtually all industries. Explore what blockchain will mean for big data and your industry. Gain insights on:

    • Potential use across industries
    • How big data and blockchain work together
    • Practical applications of this emerging technology

    Develop a strategy to make blockchain work for your organization.

  • 4:30 PM
    Conference Adjourns
February 8, 2018
February 9, 2018
  • 9:00 AM - 12:00 PM
    Workshop A
    Artificial Intelligence: Leverage the Power of AI to Create Efficiencies and Improve Returns

    From enhancing business intelligence to chatting with customers, AI is already transforming the way organizations operate. Take advantage of the biggest technological revolution of our lifetime to improve your business. Create a plan to:

    1. Grasp fundamental concepts like statistics, uncertainty and Bayes networks
    2. Make the transition from analytics and big data to AI
    3. Process and extract meaning from natural language
    4. Create programs that process images and video
    5. Build intelligent bots that can communicate with customers
    6. Understand the basics of machine learning
    7. Apply AI to real business cases

    Do more with your resources using the power of AI.

  • 1:00 PM - 4:00 PM
    Workshop B
    Machine Learning: Process More Data, More Efficiently to Achieve a Competitive Advantage

    Machine learning allows computers to learn without being explicitly programmed. This can allow your computers to work independently, processing more data than you ever could manually. Develop a plan to:

    1. Apply linear and logistic regression to make predictions
    2. Create models that generalize to new examples they have not seen
    3. Apply neural networks for applications like recognizing speech
    4. Optimize machine learning algorithms
    5. Create support vector machines for supervised learning
    6. Apply unsupervised learning to create models that help better understand data
    7. Identify real-world applications to improve your business with machine learning

    Apply machine learning to improve the way you process data.

  • 1:00 PM - 4:00 PM
    Workshop C
    Building an Advanced Analytics Team to Drive Results
    Dr. Eugene Wen
    Vice President, Group Advanced Analytics, Manulife

    An analytics program is only as good as the team that supports it. Ensure the success of your program by assembling a team of analysts, data scientists and others with the right skill sets and develop a strategic plan to achieve results. This workshop will address the following practical topics:

    1. Understand corporative strategic directions and determine where data analytics should sit in your organization
    2. Identify the skills your organization needs
    3. Recruit, train and retain skilled data professionals
    4. Establish strategic goals for your team
    5. Improve collaboration & integration with businesses
    6. Assess options in building COEs
    7. Deliver results and create business value

    Improve business results by assembling an advanced analytics team.

February 9, 2018

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