Philadelhia DAMA





Come in from the COLD!!!!
Save the date and join us as DAMA Philadelphia heads back to Center City Philadelphia
When:     Wednesday, March 9, 2016
Time:      8:30 AM - 3:30 PM
Where:   Cigna Center City
2 Liberty Place, 3rd floor
1601 Chestnut Street,
Featured Speakers include
  * Karen Lopez who will present 'Data Modeling Contentious Issues' (an interactive session with audience voting and a range of topics in Data Modeling)
  * Anil Mahadev who will present 'Data Modeling in the Cloud'.
Our breakfast sponsor is Health Link Dimensions
Our lunch and second speaker sponsor is IDERA.
We extend a special welcome to the SQL PASS / PSSUG community to this meeting.
"Data Modeling Contentious Issues"

A highly interactive and popular session where attendees evaluate the options and best practices of common and advanced data modeling issues, such as:

  • ·Party/party role
  • ·Natural vs. surrogate keys
  • ·Agile & other modern methods
  • ·Who does what?
  • ·Data type precision vs delivery time
  • ·Standards vs proprietary Modeling
  • ·Data Modeling patterns

...and more.

Participants in this session will be presented with an issue along with a range of responses or possible solutions. Participants will vote on their preferred response, then the group as a whole will discuss the results, along with the merits of each possible response. If the specific issue has been discussed in other presentations, a summary of the responses of the other groups will be presented. The goal of this workshop is to help practitioners identify potential points of conflict in data modeling, as well as alternative approaches to resolving the issues.

About Karen Lopez

Karen López is a principal consultant at InfoAdvisors, Inc., a Toronto-based consulting firm. Karen has spoken at several DAMA conferences and DAMA Chapters. She has 20 years of experience in project and data management on large, multi-project programs. Karen specializes in the practical application of data management principles.

She wants you to love your data.