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Physical Data Modeling Blunders
And How to Avoid Them



Karen Lopez
Sr. Project Manager
Abstract

What’s going on in your physical data model? How many people can
or will update it to match the reality of what’s going on in your
databases? Who decides what goes into the physical model? In this
presentation we discuss 5 physical data modeling mistakes that cost
you dearly: performance snags, development delays, bugs and
professional respect. Data Architects are often tasked to prepare
first-cut physical data models, yet these skills usually overlap those of
DBAs and Developers and this overlap can lead to contention,
confusion, and complacency.


With this presentation, you’ll learn about the 5 blunders, how to find
them, plus many tips on how to avoid them.
  PAGE 2
Speaker Bio

Karen López is a principal
consultant at InfoAdvisors. She
specializes in the practical
application of data management
principles. Karen is also the
ListMistress and moderator of
the InfoAdvisors Discussion
Groups at www.infoadvisors.com
and other online communities.




  PAGE 3
Agenda




The Problem
Blunders, FAILs, D’Oh’s, Faults and WTHs?
10 Tips
 PAGE 4
POLL: Who Are You?
POLL: Physical Model Much?
The Problem




 PAGE 7
Confirmation
                               Number




     Assuming Numbers are Numbers




PAGE 8
D’OH!


•Leading Zeros
•Non-Numeric
•Special Characters
•Sorting Issues
•Externally Managed Numbers

 PAGE 9
Avoid it

1. Use a numeric-ish datatype when
   there’s math involved.
2. Do your research
3. If it’s externally managed data, its
   format or composition could change at
   any time. Anticipate that.
4. Anticipate leading zeros.
5. Anticipate significant formatting,
   characters & other tricks.



  PAGE 10
Choosing the Wrong Primary Key




PAGE 11
32 + 8 + 32 + 32 + (0 to 22) = A really big key
              that only a Data Architect could love



PAGE 12
Avoid it


• Establish Primary Key standards and styles
• Smaller PKs lead to smaller indexes and
  smaller databases. Take advantage of that
• Choose PKs that do not change when data
  changes
• Understand how Identity columns work



  PAGE 13
Applying Surrogate Keys Incorrectly




PAGE 14
Applying a Surrogate Key




 PAGE 15
WTH?




 PAGE 16
Alternate Key




 PAGE 17
Avoid it


• Establish Primary Key standards and styles
• Smaller PKs lead to smaller indexes and
  smaller databases. Take advantage of that.
• Don’t forget the Business Key
• Choose PKs that do not change when data
  changes
• Understand how Identity columns work
  PAGE 18
Turning off RI for Development




PAGE 19
Blunder




 PAGE 20
RI = FK




  PAGE 21
Avoid it
• Educate team on the risks & nearly universal outcome of turning
  off RI
• Generate RI in every script




                                                • Develop test data
                                  • Develop scripts for loading data
                      • Ensure team has easy access to Data Models
  PAGE 22
Using the Defaults




PAGE 23
Defaults

 • Defaults <> Best Practices
 • Product Defaults aren’t YOUR defaults
 • Defaults might even be…faulty.


  PAGE 24
Defaulting
Faults




 PAGE 25
Avoid it

  • Create a DA Test database…and use it.
  • Test Generation Options to Test DB with
    Data
  • Generate Test Scripts, Varying Options
  • Review options with DBAs and
    Developers.
  • Choose Defaults, don’t default them
  • Save your Default Set
  PAGE 26
Other Blunders

• Using the wrong tool            •   Hand generating scripts
• Too much Subtyping              •   Failing to report issues
• Logical Flexible hierarchies    •   Denormalizing too soon
• Wrong Datatypes                 •   Failing to use constraints
• Dual updates                    •   Making performance more
• Forgetting to manage the data       important than integrity
• Duplicate Indexes               •   Completely separate logical
• Ignoring Clustering                 model
• Using overly generic design     •   Failing to take into account
  patterns                            whole environment.
• Column order                    •   Applying surrogate keys where
                                      they have no business
• Silly Long Names                •   Not testing your design
• Failing to compare              •   Ignoring reference data design

    PAGE 27
10 Tips for Avoiding Physical Modeling Blunders


1. Understand cost, benefit and risk
2. Get formal training on target technologies
3. Work near your DBAs and Developers
4. Ask DBAs about trade-offs, not just
   solutions
5. Build portfolio of performance vs. integrity
   trade-offs
 PAGE 28
10 Tips for Avoiding Physical Modeling Blunders


6. Profile Source Data
7. Build Test Databases, with Data
8. Test Scripts
9. Compare, Compare, Compare…then
   Compare some More.
10.Get More Training.

 PAGE 29
Summary    1.Don’t assume that
             numbers are….numbers
           2.Choose the right primary
             key
           3.Apply surrogate keys
             correctly
           4.Keep RI turned on
           5.Architect, don’t default




 PAGE 30
Questions?




Feedback, questions,
comments are always                     Karen@InfoAdvisors.com
appreciated.
http://www.speakerrate.com/karenlopez




    PAGE 31

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5 physical data modeling blunders 09092010

  • 1. Physical Data Modeling Blunders And How to Avoid Them Karen Lopez Sr. Project Manager
  • 2. Abstract What’s going on in your physical data model? How many people can or will update it to match the reality of what’s going on in your databases? Who decides what goes into the physical model? In this presentation we discuss 5 physical data modeling mistakes that cost you dearly: performance snags, development delays, bugs and professional respect. Data Architects are often tasked to prepare first-cut physical data models, yet these skills usually overlap those of DBAs and Developers and this overlap can lead to contention, confusion, and complacency. With this presentation, you’ll learn about the 5 blunders, how to find them, plus many tips on how to avoid them. PAGE 2
  • 3. Speaker Bio Karen López is a principal consultant at InfoAdvisors. She specializes in the practical application of data management principles. Karen is also the ListMistress and moderator of the InfoAdvisors Discussion Groups at www.infoadvisors.com and other online communities. PAGE 3
  • 4. Agenda The Problem Blunders, FAILs, D’Oh’s, Faults and WTHs? 10 Tips PAGE 4
  • 8. Confirmation Number Assuming Numbers are Numbers PAGE 8
  • 10. Avoid it 1. Use a numeric-ish datatype when there’s math involved. 2. Do your research 3. If it’s externally managed data, its format or composition could change at any time. Anticipate that. 4. Anticipate leading zeros. 5. Anticipate significant formatting, characters & other tricks. PAGE 10
  • 11. Choosing the Wrong Primary Key PAGE 11
  • 12. 32 + 8 + 32 + 32 + (0 to 22) = A really big key that only a Data Architect could love PAGE 12
  • 13. Avoid it • Establish Primary Key standards and styles • Smaller PKs lead to smaller indexes and smaller databases. Take advantage of that • Choose PKs that do not change when data changes • Understand how Identity columns work PAGE 13
  • 14. Applying Surrogate Keys Incorrectly PAGE 14
  • 15. Applying a Surrogate Key PAGE 15
  • 18. Avoid it • Establish Primary Key standards and styles • Smaller PKs lead to smaller indexes and smaller databases. Take advantage of that. • Don’t forget the Business Key • Choose PKs that do not change when data changes • Understand how Identity columns work PAGE 18
  • 19. Turning off RI for Development PAGE 19
  • 21. RI = FK PAGE 21
  • 22. Avoid it • Educate team on the risks & nearly universal outcome of turning off RI • Generate RI in every script • Develop test data • Develop scripts for loading data • Ensure team has easy access to Data Models PAGE 22
  • 24. Defaults • Defaults <> Best Practices • Product Defaults aren’t YOUR defaults • Defaults might even be…faulty. PAGE 24
  • 26. Avoid it • Create a DA Test database…and use it. • Test Generation Options to Test DB with Data • Generate Test Scripts, Varying Options • Review options with DBAs and Developers. • Choose Defaults, don’t default them • Save your Default Set PAGE 26
  • 27. Other Blunders • Using the wrong tool • Hand generating scripts • Too much Subtyping • Failing to report issues • Logical Flexible hierarchies • Denormalizing too soon • Wrong Datatypes • Failing to use constraints • Dual updates • Making performance more • Forgetting to manage the data important than integrity • Duplicate Indexes • Completely separate logical • Ignoring Clustering model • Using overly generic design • Failing to take into account patterns whole environment. • Column order • Applying surrogate keys where they have no business • Silly Long Names • Not testing your design • Failing to compare • Ignoring reference data design PAGE 27
  • 28. 10 Tips for Avoiding Physical Modeling Blunders 1. Understand cost, benefit and risk 2. Get formal training on target technologies 3. Work near your DBAs and Developers 4. Ask DBAs about trade-offs, not just solutions 5. Build portfolio of performance vs. integrity trade-offs PAGE 28
  • 29. 10 Tips for Avoiding Physical Modeling Blunders 6. Profile Source Data 7. Build Test Databases, with Data 8. Test Scripts 9. Compare, Compare, Compare…then Compare some More. 10.Get More Training. PAGE 29
  • 30. Summary 1.Don’t assume that numbers are….numbers 2.Choose the right primary key 3.Apply surrogate keys correctly 4.Keep RI turned on 5.Architect, don’t default PAGE 30
  • 31. Questions? Feedback, questions, comments are always Karen@InfoAdvisors.com appreciated. http://www.speakerrate.com/karenlopez PAGE 31