Data Modeling Under Fire – a special all-day data modeling training course

 

Friday, October 15, 2010   8:00 – 5:00

Registration and Breakfast 8:00.  Program 9:00 to 5:00.

Towers-Watson, Philadelphia

Price includes class registration, continental breakfast and buffet lunch.
Price is $200 for DAMA members and $250 for non-members.
Price includes one full year DAMA membership for non-members.
Register three from the same organization for $500.

Register early!  This program was held recently by DAMA NYC and sold out quickly.

A number of recent trends have placed data modeling under fire. Will data modeling survive them? What has changed in data modeling? What needs to change?

 

DAMA Philadelphia / Delaware Valley will hold a special presentation to address these issues. The presentation will have two primary parts. The first part will address Agile Modeling and related concepts. The second part will address a variety of contemporary trends that appear (in whole or in part) to provide opposition to data modeling.

 

Data Modeling Under Fire

This first part of the presentation will examine agile data modeling and refactoring of databases. Both are intended as evolutionary development approaches. For the sake of definition, an evolutionary method is one that is both iterative and incremental in nature, and an agile method is evolutionary and highly collaborative in nature. Refactoring uses a small change to source code to improve its design without changing its semantics. Refactoring is now being applied to databases.

Haven’t professional data modelers always defined data modeling as iterative, incremental and evolutionary? Or have they? If so, then what is so different about agile approaches? Are they real, and do they add real value, or are they simply a justification of the attitude that “we never have time to do it right but we always have time to do it over!”? The presentation will take an honest look at data modeling practices, and an equally honest look at agile methods, and will compare the two by contrasting the pros and cons of each approach. It will also take a look at current development trends. How much new development do we do anyway? How much is major maintenance, and how much is minor maintenance? Finally, the presentation will recommend some changes that can be made to data modeling practices to make them more agile – without sacrificing the characteristics of a good data model. It will address the types of change that can be made to a data model. It will address how to do designs that don’t have to be changed. How can you incorporate change into a data model from the start? It will address how to validate a data model before it goes into production (or even into system test) to ensure it will work successfully when its feet hit the floor and can even survive months if not years error-free. What is a healthy attitude of data modeling to time and change? What part should these play in OLTP, data warehouse and master data projects? What do we now think about dimensional modeling?

Domain-driven design (DDD) is an approach to developing software for complex needs by deeply connecting the implementation to an evolving model of the core business concepts. The premise of DDD is:

·        Focus on the core domain and domain logic

·        Base complex designs on a model

·        Collaboration between technical and domain

 

Agenda

Agile Data Modeling

  • Definition of agile methods
  • Definition of refactoring
  • Domain-driven development
  • Database refactoring
  • Ivory tower vs. thoughtful development
  • The levels of data modeling
  • Types of projects: new vs. maintenance
  • Evolutionary database development
  • The process of database refactoring
  • Validating a data model
  • ER modeling and UML modeling
  • Pitfalls of use case driven data modeling
  • Designing for change
  • Database refactoring strategies
  • Classifying refactoring changes

Dimensional Modeling – The Current Perspective

  • The original perspective
  • What we’ve learned

Dealing with Complexity

  • Complexity in time
  • Dealing with change

Domain Driven Design

  • Using business language
  • Defining context
  • The value proposition
  • Identity and life of entities
  • Value objects describing things
  • Aggregates combine entities
  • Domain services and operations
  • Repositories manage aggregates
  • Storing data in databases

 

 

 

 

 

 

 

Brief Bio

Tom Haughey is considered one of the four originators of Information Engineering in America. He has specialized in data management since 1983 in both consulting and training. He has focused on practical and rapid development methods. For over two decades he has been delivering successful data management solutions in the area of information architecture, business intelligence, master data management, database, data modeling, data warehousing and OLTP (On-line transaction processing). He has worked in many industries such as insurance, consumer products, finance, government and pharmaceutical. His courses on data management, data warehousing, and rapid development have been delivered to Fortune 1000 companies around the world. He has worked on the development of seven different CASE tools, over 40,000 copies of which have been sold to date. He was formerly Chief Technology Officer for the Pepsi Bottling Group and Director of Enterprise Data Warehousing for Pepsico. He was also formerly Vice President of Technology for Computer Systems Advisers, who marketed the CASE tools called POSE and SILVERRUN. He wrote his own CASE tool in 1984. He formerly worked for IBM for 17 years as a Senior Project Manager. He is an author of many articles on Data Management, Information Engineering and Data Warehousing, and was contributor to DMReview’s Ask The Experts Column and to CA’s Data Modeling blog.