The Premier Organization for Data Professionals

All Events

Upcoming events

    • Wednesday, June 19, 2019
    • 8:30 AM - 11:30 AM
    • University of Minnesota - Carlson Analytics Lab? (CONFIRMED)



    Abstract  


           

    Biography

    Maher Lahmar is the Head of Data Science at Google Customer Solutions. He leads a team of data scientists who help drive revenue growth and operational effectiveness in the Sales and Marketing organizations of Google Ads.

     

    Prior to Google, he served as a Senior Offering Manager within the Watson Customer Engagement organization where he drove the strategy and development of omni-channel solutions catering to retail.  Prior to joining IBM, he acted as the Director of Global Customer Insights and Analytics at Walmart leading the development of a suite of Assortment Planning tools and managing the Test and Measurement CoE for Walmart US and Sam’s Club.  He also worked at Target where he lead a team of data scientists and collaborated with vendors on developing and implementing advanced analytical solutions for merchandising and pricing stakeholders.  

     

    At earlier stages of his career, Maher held a Scientist position at PROS, a Pricing and Revenue Optimization software company where he developed predictive analytical solutions for Fortune 500 clients. He also served as a faculty at the University of Houston and University of Minnesota. 

     

    Maher holds a Ph.D. in Industrial Engineering from the University of Minnesota and is a Certified Agile Practitioner. He has been a member of Informs (Institute of Operations Research and Management Sciences) since 1998 and served as the General Chair of the 2017 Informs Analytics Conference.



    Agenda

    8:30 Registration & Networking
    9:00 Opening Remarks
    9:15 - 11:30  Presentation

    11:30 - 11:45  Open Q&A

     

    Location



    Directions

     


     

     


     

    • Wednesday, July 17, 2019
    • 8:30 AM - 11:30 AM
    • Cargill (CONFIRMED)


    Abstract  


           

    Biography

         






    Agenda

    8:30 Registration & Networking
    9:00 Opening Remarks
    9:15 - 11:30  Presentation

    11:30 - 11:45  Open Q&A

     

    Location



    Directions

     


     

     


     

    • Wednesday, August 21, 2019
    • 8:30 AM - 11:30 AM
    • Securian Financial Group, St Paul (CONFIRMED)

    Abstract  


           

    Biography

         






    Agenda

    8:30 Registration & Networking
    9:00 Opening Remarks
    9:15 - 11:30  Presentation

    11:30 - 11:45  Open Q&A

     

    Location



    Directions

     


     

     


     

    • Monday, September 16, 2019
    • 8:30 AM - 11:30 AM
    • TBD

      

    Speaker 1: Prashanth H Southekal

    Speaker 2: Salema Rice


    Prashanth's Abstract  

    Machine Learning (ML) is a form of Artificial Intelligence (AI) that enables computers to automatically learn and adapt using large volumes of quality data sets. The main goal of ML is to learn from the previous data patterns and make future predictions. Today, ML powers technologies such as facial recognition, fraud prevention, consumer shopping patterns, equipment failure, and even self-driving cars. However, the field of ML is vast and complex and this 3-hour tutorial with three basic modules is your entry into the world of ML. This training is designed for analysts, managers, and executives across any industry sector who want to get a broad overview of key ML concepts and techniques. 


    The first module provides an overview of the basic concepts and building blocks of ML.  This module covers the 5 main types of Analytics and the 3 types of ML. Given that ML heavily involves techniques from both statistics and computer science, the next two modules cover these two areas. Module 2 provides an overview of statistical concepts such as data distributions, sampling, correlation, statistical tests (such as T-Tests and ANOVA) and more. The third module is on the computer science aspects and covers ML algorithms such as Decision Trees, Support Vector Machines (SVM), Logistic Regression, Linear Regression, and Clustering. In all the three modules the emphasis is on the ML concepts and their relation to the real and enterprise/business world in plain simple English. This is not a ML programming tutorial.

     

          

    Biography

    Dr. Prashanth H Southekal is the Managing Principal of DBP-Institute (www.dbp-institute.com), a boutique Data Analytics and Metrics firm that specializes in monetizing data for business enterprises. He brings over 20 years of Data and Information Management experience consulting/working for companies such as SAP AG, Shell, Apple, P&G, and General Electric working in Canada, India, US, Belgium, UK, and Spain. He has presented his works on Analytics, Solution and Data Architecture, KPI based Dashboards, and Data Monetization in IEEE journals, universities, and industry conferences. He is also an adjunt faculty at the University of Alberta (UoA) in Edmonton, Canada.Dr. Southekal has published two books on Information Management including the most popular - Data for Business Performance. 




    Speaker 2:

    Salema's Abstract  


           

    Biography





    Agenda

    8:30 Registration & Networking
    9:00 Opening Remarks
    9:15 - 11:30  Presentation

    11:30 - 11:45  Open Q&A

     

    Location



    Directions

     


     

     


     

    • Wednesday, October 16, 2019
    • 8:30 AM - 11:30 AM
    • Allianz Life, St. Louis Park (CONFIRMED)

    Abstract  


           

    Biography

         






    Agenda

    8:30 Registration & Networking
    9:00 Opening Remarks
    9:15 - 11:30  Presentation

    11:30 - 11:45  Open Q&A

     

    Location



    Directions

     


     

     


     

    • Wednesday, November 20, 2019
    • 8:30 AM - 11:30 AM
    • TBD

    Abstract  


           

    Biography

         






    Agenda

    8:30 Registration & Networking
    9:00 Opening Remarks
    9:15 - 11:30  Presentation

    11:30 - 11:45  Open Q&A

     

    Location



    Directions

     


     

     


     

    • Wednesday, December 11, 2019
    • 8:30 AM - 11:30 AM
    • TBD

    Abstract  


           

    Biography

         






    Agenda

    8:30 Registration & Networking
    9:00 Opening Remarks
    9:15 - 11:30  Presentation

    11:30 - 11:45  Open Q&A

     

    Location



    Directions

     


     

     


     

Past events

Wednesday, May 15, 2019 Thank You For Sharing My Data: Making the case for new and emerging, top level data roles through data governance
Wednesday, April 17, 2019 Dawn Michels: Right Sizing Data Management for a small to medium size organization
Wednesday, March 20, 2019 Leading Information Governance Without a Formal Data Strategy
Wednesday, February 20, 2019 Harnessing Data for Business Management and Decision Making : Nice Healthcare Case Study
Thursday, January 17, 2019 A Framework for Identifying Business Value Through Blockchain Technology
Wednesday, November 14, 2018 Data Engineering - The Hottest New Job
Wednesday, October 17, 2018 Dan Myers: Real World Data Quality Using the Conformed Dimensions of Data Quality
Monday, September 24, 2018 2018 DAMA Day: Peter Aiken - Crafting A Strategy for Your Data: Your most powerful, yet underutilized and poorly managed organizational asset.
Wednesday, August 15, 2018 Dr. Karl Smith: Project Management Methodologies
Wednesday, July 18, 2018 Dr. Manjeet Rege: Visualizing Effectively
Wednesday, June 20, 2018 Billy Cripe/ Amanda Isaacson: The new DATA dream team: aligning with and engaging the new data debutantes: sales and marketing
Wednesday, May 16, 2018 Evan Levy: GDPR: The Seismic Shift in Marketing Analytics
Thursday, April 19, 2018 Mark Ouska: Why I Ignored Ontology and Graph DB and Why You Shouldn't
Wednesday, March 21, 2018 Todd Sicard: Blockchain & Dawn Michels: Data Management Body of Knowledge(DMBOK) Case Study
Wednesday, January 17, 2018 Luminita Vollmer: Blockchain - A Distributed Ledger
Wednesday, December 13, 2017 Dr. Phil Shelley: Data And Analytics Modernization To Cloud — Considerations And Reasons To Consider
Wednesday, November 15, 2017 Ellena Schoop: Making the Shift of Data Governance from IT to the Business
Wednesday, October 18, 2017 CANCELLED: The October Chapter Meeting has been cancelled
Tuesday, September 19, 2017 2017 DAMA Day - Tom Redman: Data Provocateurs Boot Camp
Wednesday, August 16, 2017 Frank Cerwin - Mastering Master Data Using a Service Operating Model
Wednesday, July 19, 2017 Kent Graziano: Changing the game with Cloud Data Warehousing
Wednesday, June 21, 2017 Sue Habas: Data Lineage
Wednesday, May 17, 2017 Cathy Nolan: Data Privacy
Wednesday, April 19, 2017 Anthony Algmin: Advanced Data Architecture for Big Data, IoT, and Cloud
Wednesday, March 15, 2017 Bonnie O'Neil: Agile Data: Oxymoron or Complementary?
Wednesday, February 15, 2017 Mike Striefel: Part 1: Big Data - An overview of tools and capabilities; Carolyn Lewis: Part 2: The New DAMA 'Certified Data Management Professional® (CDMP®)' certificate
Wednesday, January 18, 2017 DAMA-MN Board of Directors Meeting - Members Welcome
Wednesday, December 14, 2016 Jay Zaidi: Age of Data
Wednesday, November 16, 2016 Michael Blaha: A Database Reverse Engineering Case Study
Wednesday, October 19, 2016 Missy Wittmann: Roadmap to an Enterprise Logical Data Model
Tuesday, September 20, 2016 2016 DAMA Day - Len Silverston: Drowning in Data, Starving for Wisdom!: How to Apply Wisdom to Traditional as well as New Trends in Information Management
Wednesday, August 17, 2016 Wesley Rhodes: Technologies of Disruption
Wednesday, July 20, 2016 Dalton Cervo: Metadata Management as a Key Component to Data Governance, Data Stewardship, and Data Quality
Wednesday, June 15, 2016 Gordon Everest: Conceptual vs. Logical vs. Physical: Stages of Data Modeling
Wednesday, May 18, 2016 Janet Lichtenberger: Developing and Implementing Policies and Standards to Manage Data as an Enterprise Asset
Wednesday, April 20, 2016 Matt McGivern: Regulated Data Governance in the Financial Sector and BCBS 239
Wednesday, March 16, 2016 Enterprise Data World (EDW) 2016 Preview - 1. Dawn Michels: Metadata Updates - What if We Got It Wrong? 2. Susan Von Fruke: Applying Library and Information Science Disciplines to DMBOK Knowledge Areas
Wednesday, February 17, 2016 Enterprise Data World (EDW) 2016 Preview - Luminita Vollmer: A Data Warehouse Now, Using Methods for the Future
Wednesday, January 20, 2016 DAMA-MN Board of Directors Meeting - Members Welcome
Wednesday, December 16, 2015 Rebecca Frederick: Vendor Risk Management
Wednesday, December 16, 2015 DAMA-MN Chapter Officer Elections
Wednesday, November 18, 2015 Dan McCreary: Modern Metadata Management in the NoSQL World
Wednesday, October 21, 2015 Michele Goetz: Building the Trust Trinity to Lead Data Governance
Monday, September 21, 2015 2015 DAMA Day - Kelle O'Neal: Sustainable Data Governance and Roles & Responsibilities of a Data Management Organization
Wednesday, August 19, 2015 Charlie Vollmer: Powerful Machine Learning Anyone Can Do
Wednesday, July 22, 2015 Michael Scofield: Avoiding Catastrophe When Importing Data and Using It in Your Enterprise
Tuesday, June 16, 2015 Data Modeling with Big Data, NoSQL and other Modern Data Platforms – The Process with Karen Lopez
Wednesday, May 20, 2015 CANCELLED: May Meeting Has Been Cancelled
Wednesday, April 15, 2015 Charlie Betz: IT4IT
Wednesday, March 18, 2015 Dawn Michels / Luminita Vollmer : Enterprise Data World Preview
Wednesday, February 18, 2015 DAMA Board of Directors Panel Discussion
Wednesday, January 21, 2015 DAMA Board of Directors Panel Discussion
Wednesday, December 17, 2014 Dan McCreary 2nd Generation NoSQL Databases
Wednesday, November 19, 2014 Matthew Israelson: Back-End Structures & Front End Visualization
Wednesday, October 15, 2014 David Wormald - Semantic Discovery
Monday, September 15, 2014 2014 DAMA Day - David Marco: Demystifying Meta Data Management
Wednesday, August 20, 2014 John Bauer: I like Big Data and I don’t know why
Wednesday, July 16, 2014 Dr. Phil Shelley: BIG DATA
Wednesday, June 18, 2014 Josh More: Job Recon - Using Hacking Skills to Land the Job of your Dream
Wednesday, May 21, 2014 Johnny Gay: Data Modeling Tool Tips and Techniques & Gordon Everest: Test your Data Modeling Skills
Wednesday, April 16, 2014 Luminita Vollmer: Title: The EIM Reference Architecture – A journey to the center of the Enterprise
Wednesday, March 19, 2014 Billy Cripe: Social Competitive Intelligence - Putting Data Insights Into Action
Wednesday, February 19, 2014 Ross McNeely: Data Modeling with Graph Databases
Wednesday, January 15, 2014 Dave Haertzen: "Data Structures for Analytics" and "Modeling Your Customer"
Wednesday, December 18, 2013 Saeed Rahimi: NoSQL 101: Big Data Analytics – Scrub with Pig, Store in HBase, And Analyze with Hive
Wednesday, November 20, 2013 Linda Finley: Definition and Practical Value of Business Architecture
Wednesday, October 16, 2013 Deepak Bhaskar: Data Governance and Data Quality programs: Better Outcomes, Worthwhile Change, for Any Organization
Monday, September 16, 2013 2013 DAMA Day - Danette McGilvray: Increasing Project Success through Data Quality and Governance
Wednesday, August 21, 2013 Lillian Pierson: The Data Revolution - From Data Science and Big Data to the Geospatial Revolution and Digital Humanitarian Response
Wednesday, July 17, 2013 Josh More: Lean Security: Practical Uses in the Real World
Wednesday, June 19, 2013 Billy Cripe: Building Collaboration With Intelligent Unstructured Data Management
Wednesday, May 15, 2013 Michael Scofield: Data Visualization: Converting Raw Data to Useful Information
Wednesday, April 17, 2013 Program To Be Announced
Wednesday, March 20, 2013 Andrea Thomsen: 1. Abstract - Creating and Selling an Enterprise Information Management Strategy; Luminita Vollmer: 2. Abstract - Data Architecture and Data Governance - The Not so Siamese Twins in IT
Wednesday, February 20, 2013 Richard Howey: Why Should Business Invest in Data?
Wednesday, January 16, 2013 Randy Hedegaard: 1. Abstract - Data Governance and Data Quality at the Minnesota Pollution Control Agency; David Haertzen: 2. Abstract - Profitable Analytics
Wednesday, November 21, 2012 Lean Security and Data Governance - An Evolutionary Tale
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