KeynotesOct 27. Keynote Day 1. David Marco (Chicago - EWSolutions). In 2004 David Marco was named the “Melvil Dewey of Metadata” by Crain’s Chicago Business as he was selected to their very prestigious “Top 40 Under 40” list. He followed up this honor in 2007 by being named one of DePaul University’s “Top 14 Alumni Under 40”. In 2008 David Marco was enshrined into the DAMA Data Management Hall of Fame (Professional Achievement Award) 

Focus: Establishing and Developing a World Class Data Management Programme. David Marco is the author of the widely acclaimed, top-selling books “Universal Meta Data Models” and “Building and Managing the Meta Data Repository” which were translated into Mandarin (Chinese).  In addition, he is a coauthor of “Impossible Data Warehouse Situations and Solutions From The Experts” and “Data Resource Management”.  David Marco has published hundreds of articles some of which have been translated into Mandarin, Russian, Portuguese and others.  

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Oct 28. Keynote Day 2. Kevin Waugh (Formerly Menlo Park - Facebook &  now Edmonton - Google Deepmind (UofA). Large-scale Data Collection and Machine Learning Pipelines — Is  machine learning a magic hammer that can effortlessly solve any problem? This talk aims to clarify and remove this mystique.

Focus:  Interest in machine learning has skyrocketed at companies of all sizes.  The value of the largest internet companies, e.g., Google and Facebook, is derived increasingly from their machine-learning-based advertising systems. Traditional retailers, like Target and Walmart, have also developed machine learning systems that realize tangible value from their troves of data.  Kevin will discuss how the large players organize their machine learning pipelines:  how they collect and store data, then use this data to train and evaluate models, and finally how these models are deployed as part of a larger system.  He will enumerate the roles and responsibilities of the people engaged throughout these pipelines, as well as the factors that inform how they are organized.  Kevin will also discuss the history of how these pipelines have evolved, and their current forward trajectory.  Finally, he will elaborate on the types of problems that machine learning can and cannot solve and the amount of effort necessary to hone these solutions.

Dynamic Speakers. Cutting-edge Insights.

While we have confirmed many of the speakers, these are always subject to change due to travel and personal situations resulting in last minute changes.  Each of our speakers has been chosen specifically because they are locally or internationally recognized experts in their field.  
 
Check out our speaker roster ​here...

Conference Schedule

​​Oct 27 Conference Sessions
7.30am - 8.25am. Light Breakfast and Registration
8.30am - 9.30am. David Marco (Building a world class Data Management Capability)
9.30am - 10.15am. Dr. Jerry Luftman ( Preparing the C-Suite for Digital Resources Management)
10.15am - 10.30am. Coffee and Booths
10.30am - 11.15am. Dr. Bradley Jensen (Building a World Class Data Scientist Capability)
11.15am-12.00pm. Dr. Kewal Dhariwal (Certification programs: Data Scientists-machine learning, Public Sector Governance Professional, Certified Data Professionals and Cyber Security Professionals)
12.00pm - 1.25pm. Lunch and Speaker: Matt McInnis (Data Science Powered by Open Source; The Fundamentals)
1.30pm - 2.15pm. Bob Tipton (Changing Culture through vision casting and disruptive strategies: The power of what's right, not who's right)
2.15pm - 3.00pm. Dr. Krista Uggerslev (Organizing & Accessing Innovative Research - using data science)
3.00pm - 3.30pm. Coffee and Booths
3.30pm - 4.15pm. Giri Berenstein (Power to the people: new approaches to data store development)
4.15pm - 5.00pm. Kimberly Nevala (Mastering the Machine: A Checklist - Machine learning using SAS)
5.00pm - 6.30pm. Attendees Reception (Booths Area)
                                                                        
Oct 28 Conference Sessions
8.00am - 8.30am. Light Breakfast and Registration
8.30am - 9.30am. Kevin Waugh (Large-scale Data Collection and Machine Learning Pipelines)
9.30am - 10.30am. Dr. Amelia Estwick (Another Day…Another Data Breach!  How the Collection of Data and Metadata Present Cybersecurity Risks - National Cybersecurity Institute - Washington D.C.)
10.30am - 10.45am. Coffee & Booths
​10.45am - 11.45am. Karen Lopez (Cyber Security - Designing in Data Protection: Methods and Madness)
11.45am - 1.00pm. Lunch and Speaker: Ziko Rajabali (Unveil Your Email: Data Science in Every Organization)
1.00pm - 1.50pm. Dr. Ewan Affleck (Centralizing Health Records - benefits, issues and concerns)
1.55pm - 2.45pm. Dr. Louis Francescutti (How many doctors do we need after Machine Learning and Artificial Intelligence are adopted)
​2.45pm - 3.15pm. Coffee and Booths
3.15pm - 4.00pm. Kathy Rondon (Public Sector Data Governance - an intelligence community case study - the current state of tradecraft and Data curation strategies)
4.00pm-4.30pm. Patrick Chorley - Microsoft Azure Data Lake;  Tools of the Trade

Workshops

Oct 26. Tableau Master Workshop

Oct 29. SAS Workshop (Hands-on Workshop- Mark Miskiman)

Oct 29. Workshops (9.00am - 12pm)
1. Certification: Examinations Boot Camp (Morning).- Enterprise Data Analytics, Data Science, Public Sector Data Governance, Business Intelligence (Kewal Dhariwal)
2. KNIME Workshop (Iqbal Jamal)
3. Cyber Security Workshop - Dr. Amelia Estwick (Tips and Tricks for a Safer Digital Life)

Oct 29. Workshops (1.00pm - 4.00pm)
1. Certification Examinations (1pm-6pm): Take up to three examinations on a "pay-if-you-pass" basis and get credentialed at this conference (Kewal Dhariwal)
2. SAS Workshop (Hands-on Workshop- Mark Miskiman) - Join SAS for a Free workshop