Skip to content

shannonlowder.com

Menu
  • About
  • Biml Interrogator Demo
  • Latest Posts
Menu

SQL 103 – Normalized Table Design

Posted on October 3, 2011 by slowder

So last time we were discussing the difference between normalized and de-normalized database design.  We also discussed our case study, the CRM company.  We decided to begin our database design by designing normalized tables to track customers and contacts with those customers.

Let’s continue with that case today.  We want to build tables to store customers, their addresses, and their phone numbers.  Our company will receive customer information in the form of a flat file.  We need our database to hold all the information from this flat file, as well as let us conduct our business of contacting these customers.

The Source File

Column Name DataType Length Description
UniqueCustomerID VARCHAR 32 GUID to uniquely identify each customer
FirstName VARCHAR 50
MiddleName VARCHAR 50
LastName VARCHAR 100
StreetAddress VARCHAR 255
StreetAddress2 VARCHAR 255
City VARCHAR 50
State CHAR 2
Zip VARCHAR 10
PhoneNumber VARCHAR 10
CellNumber VARCHAR 10
WorkNumber VARCHAR 15
SpouseFirstName VARCHAR 255
SpouseMiddleName VARCHAR 255
SpouseLastName VARCHAR 255
SpousePhoneNumber VARCHAR 10
SpouseCellNumber VARCHAR 10
SpouseWorkNumber VARCHAR 15

Looking at the data we will receive, I want you to think about the data we’re receiving.  If you have any experience with object oriented programming, answer the following question.  How many different objects exist in this data?  If you’re not familiar with that terminology, then how many nouns do you see in this layout?

Three.

There are customers (and spouses).  There are addresses.  There are phone numbers.

Now, what is the parent object?  In other words, what one object to the other two objects both relate to?

That’s right, customers would be your parent object.  So we’ll begin by modeling that object first.  We’ll design a table that will hold data about our customers.  We want to create a table that holds just the data that relates to customers, but doesn’t relate to anything else…at least not directly.

The Customer Table

An example of what I mean by data that only relates to customers and not directly to anything else: first name, middle name, last name, and unique customer ID.  The name doesn’t refer to an address.  It doesn’t refer to  a phone number either!  When you break down a customer into its “atomic” attributes, we just have 4 in this example.

When I diagram a table, I usually draw a box, and then start listing the attributes that identify the object I’m modeling.

In this case, I’ll draw a box, and name it Customer.  Then I’ll list the attributes that relate to customers.

Since customers and spouses have these same attributes, we’re going to use the same table to store both.  That way we’re not repeating data.

Let’s Do The Same For Addresses and Phone Numbers

We’re going to draw addresses and phone numbers the same way.  We’re only going to include the attributes that relate to addresses in the Address table, and we’re only going to include the attributes that relate to phone numbers in the PhoneNumber table.

Now that we’ve drawn these two tables, we’re not done with these tables. We have to relate spouses to spouses, addresses to customers, and phone numbers to customers.  But we’re going to leave that until next time.

Until then, if you have any questions, send them in.  I’m here to help!

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recent Posts

  • A New File Interrogator
  • Using Generative AI in Data Engineering
  • Getting started with Microsoft Fabric
  • Docker-based Spark
  • Network Infrastructure Updates

Recent Comments

  1. slowder on Data Engineering for Databricks
  2. Alex Ott on Data Engineering for Databricks

Archives

  • July 2023
  • June 2023
  • March 2023
  • February 2023
  • January 2023
  • December 2022
  • November 2022
  • October 2022
  • October 2018
  • August 2018
  • May 2018
  • February 2018
  • January 2018
  • November 2017
  • October 2017
  • September 2017
  • August 2017
  • June 2017
  • March 2017
  • February 2014
  • January 2014
  • December 2013
  • November 2013
  • October 2013
  • August 2013
  • July 2013
  • June 2013
  • February 2013
  • January 2013
  • August 2012
  • June 2012
  • May 2012
  • April 2012
  • March 2012
  • February 2012
  • January 2012
  • December 2011
  • November 2011
  • October 2011
  • September 2011
  • August 2011
  • July 2011
  • June 2011
  • May 2011
  • April 2011
  • March 2011
  • February 2011
  • January 2011
  • December 2010
  • November 2010
  • October 2010
  • September 2010
  • August 2010
  • July 2010
  • June 2010
  • May 2010
  • April 2010
  • March 2010
  • January 2010
  • December 2009
  • November 2009
  • October 2009
  • September 2009
  • August 2009
  • July 2009
  • June 2009
  • May 2009
  • April 2009
  • March 2009
  • February 2009
  • January 2009
  • December 2008
  • November 2008
  • October 2008
  • September 2008
  • August 2008
  • July 2008
  • June 2008
  • May 2008
  • April 2008
  • March 2008
  • February 2008
  • January 2008
  • November 2007
  • October 2007
  • September 2007
  • August 2007
  • July 2007
  • June 2007
  • May 2007
  • April 2007
  • March 2007
  • February 2007
  • January 2007
  • December 2006
  • November 2006
  • October 2006
  • September 2006
  • August 2006
  • July 2006
  • June 2006
  • May 2006
  • April 2006
  • March 2006
  • February 2006
  • January 2006
  • December 2005
  • November 2005
  • October 2005
  • September 2005
  • August 2005
  • July 2005
  • June 2005
  • May 2005
  • April 2005
  • March 2005
  • February 2005
  • January 2005
  • November 2004
  • September 2004
  • August 2004
  • July 2004
  • April 2004
  • March 2004
  • June 2002

Categories

  • Career Development
  • Data Engineering
  • Data Science
  • Infrastructure
  • Microsoft SQL
  • Modern Data Estate
  • Personal
  • Random Technology
  • uncategorized
© 2025 shannonlowder.com | Powered by Minimalist Blog WordPress Theme