Big Challenges in Data Modeling: Data Modeling at High Speed

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It's May, which brings this former Hoosier thinking of racetracks and Indy cars. I'm also a runner and that means I'm always thinking about pace and timings…and feeling guilty about not training hard enough.

This got me musing about how data modelers can speed up the data modeling process -- not just during a development projects, but at all points in our work day. So let's have a discussion about.

In this month's webinar, we'll talk about:

The Need for Speed
Sprints, marathons and training
Race cars, horses, carts, and feet
Qualifiers and Races
Pace cars
Backseat drivers
Rules, tickets and enforcement
Fads, gadgets and automation
Red, yellow, green and checkered flags
How do you know when to stop racing?

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Big Challenges in Data Modeling: Data Modeling at High Speed

  1. 1. YourModerator Karen Lopez Sr. Project Manager / Architect Infoadvisors @datachick #BCDModeling YourPanelist Donna Burbank VP Information Management Services, Enterprise Architects @donnaburbank Carol Lehn Database Designer, PepsiCo @lehnca
  2. 2. The Need for Speed Faster Data Models…and Data Modelers Karen Lopez
  3. 3. Welcome! #BCDModeling Chat Q&A Slides Aftershow 2
  4. 4. Need for Speed Sprints, marathons and training Race cars, horses, carts, and feet Qualifiers and Races Rules, tickets and enforcement Fads, gadgets and automation Red, yellow, green and checkered flags How do you know when to stop racing? 3
  5. 5. Sprints, Marathons & Training Agile & SCRUM Training versus racing Sprints LSDs Walkbreaks Hurdles Rest 4
  6. 6. Make it faster… 1. Know the process/methodology 2. Refuse to sprint a marathon 3. Insist on walk breaks 4. Insist on resources for maintenance 5. Put hurdles in writing, then report on their status 5
  7. 7. Race cars, Horses & Feet Maintaining cars, horses and feet Pit crew Training the crew Spare parts & shoes Upgrades 6
  8. 8. Make it faster… 1. Maintain stuff 2. Train your team mates 3. Have spares 4. Don’t use old tools 5. Use professional tools 7
  9. 9. “ ” Trained team members put up fewer obstacles and get their own jobs done faster. - Karen Lopez Quote me… 8
  10. 10. Qualifiers & Races Resumes versus Skills Tests versus portfolios Size matters Collaboration matters more 9
  11. 11. “ ” In my observations, the project gains from having an experienced data modeler: 2-3x faster to deliver usable models. - Karen Lopez Quote me… 10
  12. 12. Make it faster… 1. Hire good people with real world experience 2. Train inexperienced people 3. Mentor inexperienced people 4. Rate fit high 11
  13. 13. Rules, Tickets and Enforcement Our Rules Your Rules Inspection Automation 12
  14. 14. Make it faster… 1. Automate everything you can, and more 2. Inspect and report, don’t tattletale 3. Log it in issue management system 13
  15. 15. Fads, Gadgets and Automation Methodologies Macros & Scripts Lazy Data Modeler is Best Gadgets, Tablets, Laptops 14
  16. 16. Make it faster… 1. Automate everything you can, and more 2. Be lazy…automate more… 3. Make use of modern technology 15
  17. 17. “ ” The best data modeler is a lazy data modeler - Karen Lopez Quote me…. 16
  18. 18. Red, Yellow, Green and Checkered flags Priorities Perfection versus success Deliver! 17
  19. 19. Make it faster… 1. Automate everything you can, and more 2. Understand deliverables…yours versus theirs 3. Do maintenance during down times 4. Have a pit crew 18
  20. 20. How do you know when to stop racing and go back to training? 19

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