We have described the normalization (first normal form, second normal form ..... upto fifth normal form) in simple and easy to understand language. We at BIWHIZ are committed to equip you with the hottest skills of BI, Analytics, Big Data, Database and Data Science.

1. Learn BI, Analytics and Big Data
Module: Normalization

2. Normalization
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Normalization is a set of rules to allocate data to
tables in such a way as to minimize the
redundancy and to minimize certain anomalies
related to insert, delete and update of data.
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3. Normalization
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Anomalies
A major objective of data normalization is to avoid modification anomalies.
These come in three flavors:
• An insertion anomaly is a failure to place information into all the places in
the database. In a properly normalized database, information about a new
entry needs to be inserted into only one place in the database.
• A deletion anomaly is a failure to remove information about an existing
database entry from all places. In a properly normalized database, the
entry needs to be deleted from only one.
• A update anomaly is a failure to update information about an existing
database entry from all places.
All three kinds of anomalies are highly undesirable, since their occurrence
constitutes corruption of the database.
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4. Normalization
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First Normal Form
• A Relations is said to be in First Normal Form (1NF) when it contains no
multi-valued attribute, i.e. every attribute must contain at most one data
value.
• In other words a table is in first normal form if all the key attributes have
been defined and it contains no repeating groups.
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5. Normalization
First Normal Form
Example: Let us assume an ORDER table as below:
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ORDER
order_id customer_id product1 product2 product3
123 456 abc1 def1 ghi1
456 789 abc2
This structure creates the following problems:
•Order 123 has no room for more than 3 products.
•Order 456 has wasted space for product2 and product3.
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6. Normalization
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First Normal Form
In order to create a table that is in first normal form we must extract the
repeating groups and place them in a separate table.
We have removed 'product1', 'product2' and 'product3', so there are no repeating groups.
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ORDER
order_id customer_id
123 456
456 789
ORDER_LINE
order_id product
123 abc1
123 def1
123 ghi1
456 abc2

7. Normalization
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Second Normal Form
A relation is said to be in 2nd Normal Form if
• The relation is in 1st Normal Form
• Every non key attribute is fully functionally dependent on the whole of the
primary key (i.e. there are no partial dependencies).
1. Anomalies can occur when attributes are dependent on only part of a
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multi-attribute (composite) key.
2. A relation is in second normal form when all non-key attributes are
dependent on the whole key. That is, no attribute is dependent on only
a part of the key.
3. Any relation having a key with a single attribute is in second normal
form.

8. Normalization
Second Normal Form
Take the following table structure as an example:
order(order_id, cust_id, cust_address, cust_contact, order_date,
order_total)
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Here we should realize that cust_address and cust_contact are functionally
dependent on cust_id but not on order_id, therefore they are not dependent
on the whole key. To make this table 2NF these attributes must be removed
and placed somewhere else.
order_cust(order_id, cust_id, order_date, order_total)
customer(cust_id, cust_address, cust_contact)
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9. Normalization
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Second Normal Form
So what problems can occur if we do not make it into 2nd Normal Form?
It can result into
Update anomaly: If you want to update the address of a customer, need to
update in all orders made by this customer, if update is missed at any place
then data will be inconsistent.
Insert anomaly: There is no way to add a customer information he he/she has
not made any order.
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10. Normalization
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Third Normal Form
A relation is said to be in Third Normal Form if
• The relation is in Second Normal Form
• There is no transitive dependency (that is, all the non-key attributes
depend only on the primary key)
In other words, A relation is in 3NF when 'All non-key attributes are
dependent on the key, the whole key and nothing but the key'.
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11. Normalization
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Third Normal Form
An example of a 2NF table that fails to meet the requirements of 3NF is:
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Tournament Winners
Tournament Year Winner
Winner Date of
Birth
Indiana Invitational 1998 Al Fredrickson 21 July 1975
Cleveland Open 1999 Bob Albertson 28 September 1968
Des Moines
1999 Al Fredrickson 21 July 1975
Masters
Indiana Invitational 1999 Chip Masterson 14 March 1977

12. Normalization
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Third Normal Form
• Because each row in the table needs to tell us who won a particular
Tournament in a particular Year, the composite key {Tournament, Year} is a
minimal set of attributes guaranteed to uniquely identify a row. That is,
{Tournament, Year} is a candidate key for the table.
• The breach of 3NF occurs because the non-prime attribute Winner Date of
Birth is transitively dependent on the candidate key {Tournament, Year}
via the non-prime attribute Winner. The fact that Winner Date of Birth is
functionally dependent on Winner makes the table vulnerable to logical
inconsistencies, as there is nothing to stop the same person from being
shown with different dates of birth on different records.
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13. Normalization
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Third Normal Form
In order to express the same facts without violating
3NF, it is necessary to split the table into two:
Tournament Winners
Tournament Year Winner
Indiana Invitational 1998 Al Fredrickson
Cleveland Open 1999 Bob Albertson
Des Moines Masters 1999 Al Fredrickson
Indiana Invitational 1999 Chip Masterson
Winner Dates of Birth
Winner Date of Birth
Chip Masterson 14 March 1977
Al Fredrickson 21 July 1975
Bob Albertson 28 September 1968
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14. Normalization
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So we may ask what is the difference between 2nd
Normal Form and 3rd Normal Form in these two
examples?
In Order example, the customer address and customer
contact is part of the Order information as these values
might be needed for delivery purpose so they are
dependent on part of primary keys.
In Winner example, date of birth is not needed for the
transaction(win or loss ) , this is just an extra
information which is dependent only on Winner,
nothing to do with a win or loss.
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15. Normalization
Boyce-Code Normal Form (BCNF)
A relation is said to be in BCNF if
• The relation is in Third Normal Form
• And every determinant is a candidate key.
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16. Normalization
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Boyce-Code Normal Form (BCNF)
• Anomalies can occur in relations in 3NF if there is
a composite key in which part of that key has a
determinant which is not itself a candidate key.
• This can be expressed as R(A,B,C), C A where:
– The relation contains attributes A, B and C.
– A and B form a candidate key.
– C is the determinant for A (A is functionally dependent
on C).
– C is not part of any key.
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17. Normalization
Boyce-Code Normal Form (BCNF)
Take the following table structure as an
example:
• schedule(campus, course, class, time,
building)
• Take the following sample data:
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campus course class time building
East English 101 1 8:00-9:00 212 AYE
East English 101 2 10:00-11:00 305 RFK
West English 101 3 8:00-9:00 102 PPR
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18. Normalization
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Boyce-Code Normal Form (BCNF)
Note that no two buildings on any of the
university campuses have the same name, thus
BUILDING CAMPUS. As the determinant is not
a candidate key this table is NOT in Boyce-Codd
normal form.
campus course class time building
East English 101 1 8:00-9:00 212 AYE
East English 101 2 10:00-11:00 305 RFK
West English 101 3 8:00-9:00 102 PPR
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19. Normalization
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Boyce-Code Normal Form (BCNF)
• This table should be decomposed into the
following relations:
• R1(course, class, building, time)
• R2(building, campus)
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20. Normalization
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Boyce-Code Normal Form (BCNF)
What if we do not apply BCNF form??
Every time when you want to update Campus
and Building you have to check the other one
and make a corresponding update on that as
well. This can result in update anomaly.
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21. Normalization
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Fourth Normal Form
A table is in fourth normal form (4NF) if and only if it is in
BCNF and contains no more than one multi-valued
dependency.
• Anomalies can occur in relations in BCNF if there is
more than one multi-valued dependency.
• If A-- >> B and A-- >> C but B and C are unrelated, ie
A - - >>(B,C) is false, then we have more than one multi-valued
dependency.
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22. Normalization
Fourth Normal Form
Take the following table structure as an example:
info(employee#, skills, hobbies)
Take the following sample data:
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employee# skills hobbies
1 Programming Golf
1 Programming Bowling
1 Analysis Golf
1 Analysis Bowling
2 Analysis Golf
2 Analysis Gardening
2 Management Golf
2 Management Gardening

23. Normalization
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Fourth Normal Form
Exercise: Try adding a new hobby??
This table is difficult to maintain since adding a new
hobby requires multiple new rows corresponding to
each skill.
This problem is created by the pair of multi-valued
dependencies EMPLOYEE# -- >>SKILLS and EMPLOYEE#--
>>HOBBIES. A much better alternative would be to
decompose INFO into two relations:
• skills(employee#, skill)
• hobbies(employee#, hobby)
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24. Normalization
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Fifth Normal Form
A table is in fifth normal form (5NF) or Projection-Join
Normal Form (PJNF) if it is in 4NF and it cannot have a
lossless decomposition into any number of smaller tables.
In another words , if we try to decompose it further then
we will not be able to join them back and get the original
table.
(4th and 5th Normal Forms are applicable for Key-Only
tables so there is no question of looking at 1st, 2nd, 3rd or
BCNF normal forms, they are already there)
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25. Normalization
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Fifth Normal Form
Take the following table structure as an
example:
buying(buyer, vendor, item)
This is used to track buyers, what they buy, and
from whom they buy.
Take the following sample data:
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26. Normalization
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buyer vendor item
Sally Liz Claiborne Bags
Mary Liz Claiborne Bags
Sally Jordach Jeans
Mary Jordach Jeans
Sally Jordach Sneakers
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Fifth Normal Form
The question is, what do you do if Claiborne starts to sell Jeans? How many rows
must you create to record this fact?
The problem is there are pairwise cyclical dependencies in the primary key. That is,
in order to determine the item you must know the buyer and vendor, and to
determine the vendor you must know the buyer and the item, and finally to know
the buyer you must know the vendor and the item.
The solution is to break this one table into three tables; Buyer-Vendor, Buyer-Item,
and Vendor-Item.

27. Normalization
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Fifth Normal Form
buyer vendor
Sally Liz Claiborne
Mary Liz Claiborne
Sally Jordach
Mary Jordach
buyer item
Sally Bags
Mary Bags
Sally Jeans
Mary Jeans
Sally Sneakers
vendor item
Liz Claiborne Bags
Jordach Jeans
Jordach Sneakers

28. Questions?
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