DAMA Day - Registration OPEN. Steve Hoberman Advanced Data Modeling Challenges

Correction re: DAMA Day May 12th with Steve Hoberman

As mentioned in an early email it was stated that there would be a $50 discount off of a Technics Publishing
book for the first 50 registrants.  In fact, a $20 discount will be offered for the first 50 registrants. 

Additionally, the synopsis initially said that this would be a 2 day course.  Actually, it is only a 1 day
course.  

We apologize for any confusion.  We will be making an announcement regarding the location of the DAMA Day
later this week.

Best Regards,
Pete Stiglich
President, DAMA Phoenix

Steve Hoberman, one of the world's most well-known data modeling gurus, will be presenting Thursday, May
12th in Phoenix at the DAMA Day.  This will be a full day training session which will sharpen your modeling
skills for a very affordable rate.  

Cost is $60 for DAMA members and $100 for non-members (for non-members, price of admission includes a 1 year
DAMA Phoenix membership).

The event will start at 8:30 and go until 4.  Coffee & bagels provided at 8 am, so come early to network.  There
will also be a happy hour (cash bar) after the event.

To register, please go to http://www.dama-phoenix.org.  FIRST 50 registrants receive a $20 discount off
of a Technics Publishing book.  Click here for books published by Technics .  (e.g., DAMA DMBOK).

Please be sure to forward this email to your collegues and managers!

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Synopsis
Do you already know data modeling and want more? Take the Advanced Data Modeling Challenges Workshop! This
one-day course minimizes lecture and maximizes tackling real world data modeling scenarios. There are
eight modules to the class containing over twenty scenarios that are solved in groups then discussed with
the class.
Data Modeling Syntax. We will translate a series of business rules into different modeling notations such
as Information Engineering (IE), Integration Definition for Information Modeling (IDEF1X), and the
UML Class Diagram.

Data Modeling Guidelines. Modeling is far from an exact science and in this module we will face several
areas where guidelines are critical. We will determine when to use each of five different data models for
capturing a ragged and unbalanced hierarchy. In another scenario, we will decide whether to use a lookup
entity, a generic lookup entity, or no lookup at all. We will explore where new technologies will lead to
new classword hierarchies. We will decide when to use b-tree versus bitmap indexes.

 Business Intelligence. We will clarify the meanings of a number of dimensional modeling terms in our field
such as factless fact, merged fact, and pivoted fact. We will then sort a series of measurements into
additive, semi-additive, and fully additive. We will build the subject area, logical, and physical
dimensional data models for a lottery analytical system.

 Enterprise Architecture. We will define the elusive canonical data model. We will then build the
relational logical enterprise data model for a publishing organization. We will answer five very
challenging questions around the marketing and usage of the enterprise data model. We will then practice
integration techniques using several standard glossaries. We will also design a metadata repository.

 Industry Data Models. We will extend a generic industry data model for a data warehouse. We will also
practice reverse engineering an existing XML-based industry data model.

New Technologies. We will identify the involvement of data analysts, data architects, data modelers, and
business users in the design of a mashup. We will capture some of the challenges with creating business
intelligence mashups (bashups for short). We will help a startup company design a cloud-based survey
application as a Software as a Service (SaaS). We will reverse engineer an XML document into a relational
logical data model.
Data Profiling. We will examine sample data to determine the validity of a data model. We will model
structured, semi-structured and unstructured data for a contact application.
Roles and Responsibilities. We will determine what a data architect really does. We will determine who is
responsible when the data model is not used, or not used as intended.

Audience
This course is for anyone who has previously attended the Data Modeling Master Class or currently knows
data modeling basics and is seeking more advanced techniques. Roles include:
·         Data Modeler
·         Project Manager
·         Team Lead
·         Architect
·         Developer
·         Support Analyst
·         Data Administrator
·         Database Administrator
·         Data Analyst
·         Integration Specialist

Steve Hoberman is one of the world's most well-known data modeling gurus. He taught his first data modeling
class in 1992 and has educated more than 10,000 people about data modeling and business intelligence
techniques since then. Steve is known for his entertaining, interactive teaching and lecture style
(watch out for flying candy!), and organizations around the globe have brought Steve in to teach his Data
Modeling Master Class, which is recognized as the most comprehensive data modeling course in the
industry. Steve is the author of Data Modeling Made Simple, Data Modeler¡¦s Workbench, and Data
Modeling for the Business. He is the founder of the Design Challenges group, inventor of the Data Model
ScorecardR, and CEO of Technics Publications. You can learn more about his books and other innovative and
practical works at Technics Publications' website, www.technicspub.com. To receive Steve¡¦s
monthly Design Challenges, visit his website at www.stevehoberman.com. Steve can be reached at me <at> stevehoberman.com.

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Location announcement for May 12 DAMA Day