Just the mere mention of normalization can send shivers down the spine of the most experienced data modeler. And your team members likely hate it more than you do. But normalization does not have to be the bad word it is on most projects. It's likely that your team mates don't fully understand its benefits and that you don't fully understand why they fear it so much. In this month's webinar, Karen demonstrates the good, the bad, and the ugly of basic normalization.

1. Karen Lopez @datachick #HeartData
Heart of Data Modeling
Normalization…is not your friend
…or your Enemy

2. Yes, Please do Tweet/Share
today’s event
@datachick #heartdata

3. About Kerry
Recovering Sysadmin
Ten years of data—Varying degrees of SQL Server
Engine &
BI
Currently Senior BI
Developer/Consultant
Used to fly little
airplanes
@airbornegeek

4. Karen López
Karen has 20+ years of data and information architecture
experience on large, multi-project programs.
She is a frequent speaker on data modeling, data-driven
methodologies and pattern data models.
She wants you to love your data.

5. Data Modelers are people,
too.
...so let’s get to know you….

6. POLL: Who Are
You?

7. What Have You Worked
on?
Aug 2014

8. Attendees, be part of the webinar
Use Q&A
for formal
questions
Use chat
to discuss
with each
other

9. Plan for Today
Why topic?
Why Normalize? Denormalize?
Myths and Truths
10 Tips for Talking About and Doing Normalization

10. Confession time
I never normalize.
I don’t have the normal forms memorized, nor do I plan to
I believe understanding the principles is important
I believe normalization is NOT a process or a method. More later on
that.
Not everyone in the data world will agree with me on these things.

11. Normalization
Why this Topic?
Why NOT this Topic?

12. Normalization:It’sa
Love/HateThing.

14. Normalization, very briefly…
Developed by Ted Codd in the 70s to address update anomalies.
One fact in one place, then referenced instead of duplicated.
One fact means one to create, one item to update, one item to
delete.

15. Normalization, briefly

16. Normalization…
Is all about the keys, ‘bout the keys, ‘bout the keys…
Depends on understanding the MEANING of the keys and columns
Goes all to heck* when you have surrogate keys
Depends on the make up of the key parts (columns)

17. Normalization, briefly
1NF – all instances (rows) have the same facts
(columns). There are no repeating duplicate
columns
2NF – only applies to multi-part keys. No fact
is about just part of the key
3NF – No fact depends on another non-key
column

18. 3NF
Everyfactiseitherpartofakeyordependsuponthe
key,thewholekey,andnothingbutthekey.
….so help you Codd
Michael J Swart

19. Remember…
“Normalizationislikemarriage…
…youalwaysendupwithmorerelations”
-Data Modeling Essentials, 3rd Edition
Simsion & Witt

20. Enterprise Applications are Complex
20

21. Myths…
What Normalization is *NOT*

22. Why People Hate Normalization
Performance
Misunderstood
Taught Wrong Not Sexy

23. It’s taught wrong? Taught as a process, not a
measurement
1NF, 2NF, 3NF, etc.
Used like a grade, instead of
measurement
Magical “3NF”

24. It’s not a process on real projects
1NF 2NF 3NF 4NF BCNF

25. 10 Tips for Data Modelers
1. Stop talking about the normal forms. Just stop.
2. Study the normal forms, know the lingo. Don’t use
it, though 
3. Be able to explain the anomaly you are trying to
avoid.
4. Know your primary and alternate keys.
5. Enforce your primary and alternate keys.

26. 10 Tips for Data Modelers
6. Understand denormalization patterns.
7. Don’t take “needs to be Denormalized” as a change
request.
8. Understand other performance tuning techniques and
how to recommend them
9. Squash “JOINs are Evil” discussions. They are a feature.
10.Be flexible. That’s why we have architects & modelers.

27. Thank you, you were great.
Let’s do this next month!
Karen Lopez @datachick
#heartdata