Database Normalization 1NF 2NF 3NF
Summary
TLDRIn this video, Jesper dives into data normalization, a key concept in data architecture and digital transformation. He explains how normalization organizes structured data to enhance automation, analytics, and AI, while also contrasting it with unstructured data. Jesper introduces normalization’s core rules, focusing on the first three normal forms, and demonstrates how they transform messy data into structured tables. By breaking down complex concepts like primary keys, foreign keys, and cardinality, this video offers a practical introduction to deeper data understanding. Perfect for viewers interested in data modeling and relational databases.
Takeaways
- 📊 Data normalization is a crucial aspect of understanding structured data, making it essential for automation, analytics, and AI.
- 🔍 Data normalization helps connect structured data and provides insights into unstructured data, like information in spreadsheets or online sources.
- 📐 The relational model introduced by Edgar Codd in 1970 is a systematic way to organize and maintain data using mathematical rules.
- 🗃️ Normalization consists of five forms, with third normal form being the most commonly used in practice.
- 🔑 First normal form (1NF) ensures that each cell contains a single value, each row is unique, and there are no repeating groups in a dataset.
- 🔑 Second normal form (2NF) states that all data must depend on the primary key and any columns not depending on the primary key should be split into separate tables.
- 🔑 Third normal form (3NF) requires that non-key columns must be fully dependent on the primary key and not on any other column.
- 🔀 Foreign keys are created to link tables, ensuring relationships between entities, like employee IDs and skill IDs.
- 🧮 Data normalization simplifies complex datasets into organized, relational tables, allowing for clearer relationships and data integrity.
- 🎓 The video focuses on normalizing data up to third normal form, transforming an unnormalized table into four well-structured normalized tables.
Q & A
What is data normalization?
-Data normalization is the process of organizing data in a database by reducing redundancy and ensuring that data relationships are maintained. It typically involves structuring data into forms that allow for efficient storage and retrieval.
How does normalization relate to structured data?
-Normalization is a way to manage and organize structured data, making it easier to connect and analyze. Structured data, often stored in tables, can be normalized to ensure that relationships between data points are preserved and can be used for automation, analytics, and artificial intelligence.
What is the role of 'cardinality' in data normalization?
-Cardinality in data normalization refers to the nature of relationships between different data sets, such as one-to-one, one-to-many, or many-to-many. Understanding cardinality is crucial in the process of connecting data in a meaningful and efficient way.
What are the five rules of normalization mentioned in the video?
-The five rules of normalization, as proposed by Dr. Edgar Codd, start with the first normal form (1NF) and end with the fifth normal form (5NF). Each form introduces stricter rules for data organization, with third normal form (3NF) being the most commonly used in practice.
What is the focus of third normal form (3NF)?
-Third normal form (3NF) ensures that all non-primary key columns are fully dependent on the primary key. It eliminates transitive dependencies, meaning that non-key attributes cannot depend on other non-key attributes.
What is an example of first normal form (1NF)?
-In first normal form (1NF), each cell in a table must contain only one value, and each row must be unique. For example, if a table lists employees and their skills, the skills should be split into separate columns to comply with 1NF.
How is second normal form (2NF) different from 1NF?
-Second normal form (2NF) builds on 1NF by ensuring that all non-primary key attributes depend entirely on the primary key. If any attributes are only partially dependent on the primary key, they need to be moved into a separate table.
What is the significance of a primary key in normalization?
-A primary key uniquely identifies each row in a table and plays a crucial role in normalization. It ensures that data is organized in a way that maintains uniqueness and facilitates relationships between different tables through foreign keys.
What is a foreign key, and how is it used in data normalization?
-A foreign key is a column or set of columns in one table that refers to the primary key in another table. In normalization, foreign keys establish relationships between tables, allowing data to be connected across multiple normalized tables.
Why is normalization typically focused on up to third normal form (3NF)?
-Normalization up to third normal form (3NF) is sufficient for most practical applications, as it ensures that the data is well-organized and free of redundancy. The latter two forms (4NF and 5NF) handle more complex exceptions, but are rarely needed in everyday database management.
Outlines
🔍 Introduction to Data Normalization
Jesper introduces the concept of data normalization, emphasizing its significance in data architecture and digital transformation. He explains that data normalization is both mathematical and philosophical in nature. The focus is on structured data and its relationship with automation, analytics, and artificial intelligence. Jesper contrasts structured and unstructured data, which includes spreadsheets and online-generated data. He emphasizes that data normalization helps deepen our understanding of data connections, using data modeling to explain relationships. He also teases the concept of 'cardinality,' to be covered in a future video.
🔑 First Normal Form: Breaking Down Data
Jesper dives into the first normal form of data normalization. He explains the need to split data in spreadsheets or tables into atomic values and ensure each row is uniquely identified by a primary key. This is crucial for avoiding redundant or repeated data. He provides an example using employee skills data, where columns are separated into skill ID and skill name, ensuring each column is unique. Furthermore, repeating groups are moved into new tables. By following these rules, Jesper demonstrates how data achieves the first normal form, which is the foundation for further normalization.
📊 Second and Third Normal Forms: Refining Data Relationships
Jesper explains how second normal form extends from the first by ensuring all data depends on the primary key. He shows how skill name and skill ID, while related to each other, do not depend on the employee ID, prompting the creation of a new table. Foreign keys are introduced to link related data across multiple tables. The third normal form, which further refines the structure, ensures no column depends on any key other than the primary key. He explains that in some cases, such as job names not depending on employee ID, additional tables are needed. Ultimately, third normal form breaks one unnormalized spreadsheet into four well-structured tables.
👍 Conclusion and Call to Action
Jesper concludes by summarizing the process of normalizing data to the third normal form. He emphasizes the importance of creating well-structured, normalized tables that prevent redundancy and ensure data integrity. The video closes with an invitation to viewers to like and subscribe for more content on data architecture and transformation.
Mindmap
Keywords
💡Data Normalization
💡Structured Data
💡Unstructured Data
💡Relational Model
💡Primary Key
💡Foreign Key
💡First Normal Form (1NF)
💡Second Normal Form (2NF)
💡Third Normal Form (3NF)
💡Cardinality
Highlights
Introduction to data normalization in the context of digital transformation and structured data.
Data normalization gives a deeper understanding of structured data and how to connect it for automation, analytics, and AI.
Normalization helps in understanding relationships between different types of data, including structured and unstructured data.
Data modeling serves as a tool for understanding how data connects and how these connections tell a story.
Introduction to the concept of cardinality, which will be covered in detail in a future video.
Differentiating between process-based thinking (workflows) and data, which describes 'who we are' versus 'what we do.'
Edgar Codd's contribution to the relational model in 1970, revolutionizing how data is connected based on mathematical rules.
Normalization is a process that follows five rules to structure data, with a focus on relationships between data sets.
The first normal form (1NF) focuses on atomic values, unique identifiers, and eliminating repeating groups of data.
The second normal form (2NF) builds on 1NF by ensuring that all data depends on the primary key.
In 2NF, any column that doesn't depend on the primary key must be moved to a new table.
The third normal form (3NF) ensures that all non-key columns are dependent only on the primary key and not on any other keys.
In 3NF, data that violates the form must be split into additional tables for proper normalization.
By the end of normalization to 3NF, one unnormalized table has been transformed into four normalized tables.
Summary of the normalization process, emphasizing the importance of primary keys and relationships between tables in structured data.
Transcripts
Hi it's Jesper here i make data architecture in digital transformation videos on youtube
today i'm going to unpack data normalization the language of data data normalization is
both mathematics and philosophy and i think you will get a sense for this as the video progresses
doesn't explain everything but it gives us a deeper understanding of one particular kind of
data which is called the structure data and how to connect structured data and do more with it
such as automation analytics prediction artificial intelligence all those fun and good things and
coincidentally or perhaps not it also gives us an insight into the other side of data unstructured
data the things that sit in spreadsheets the things that being generated on the internet
put simply it's a perfect starting point for a greater and deeper understanding of data and how
data works and how data connects and what you potentially can do with it it uses a language
data modeling to show how data is connected and the nature of these connections or relationships
to tell a story this language is radically different to the language we normally use
it even has its own alphabet called cardinality but this will be covered in a separate video
we're used to process based thinking such as planning we use processes and process flows
workflows arrows etc to depict things in business how we do things the steps and the
sequences of achieving something in life we often describe ourselves as a process
if we ask that the partly to describe ourselves we often describe what we do not who we are
now it's getting philosophical a process describes what we do data describes who we are data
can exist without the process whereas the process must have data to exist you could say that data
is persistent whereas the process is not that raises the question so we thought the process
who are we very philosophical and certainly worthy of a serious dna conversation
but edgar court entered the scene and he wanted more than great in the conversations
he reduced data in data relationships into mathematics and in 1970 he released the relational
model which is a systematic approach of connecting and maintaining data based on mathematical rules
technology companies like oracle ibm microsoft amazon google used his relational model to
create their own relational databases popular open source databases like mysql are also based on it
but that's all technology let's forget about the technology for now doctor cod provides five
rules to normalize data where each rule builds on the other starting this first normal form
and ending with fifth normal form normalization is a gateway into deeper data understanding
because it addresses the thing that give data most meaning which is its relationships with other data
the magic of data lies in its relationships and types of relationships called cardinality
put simply normalization is about connecting data in the right way the first three rules of
normalization are about core basics whereas the latter two deal with exceptions hence
for practical reasons normalization typically refers to third normal form
and remember to be in third normal form it must also be in first and second normal form
so the focus today is normalization up to third normal form
first normal form is about atomic values and unique identifiers
let's say we want to model employees and their skills
and we have been handed this spreadsheet of data with the task of normalizing it
i've used spreadsheets as an example to make it easier to understand but the correct tool is
either to use table or entity first normal form specifies that the following actions need to be
taken on the data number one each cell may never contain more than one value for example a cell
cannot contain both skill id and skill name as a result we need to split into separate columns
number two each row must be unique that is one column or a combination of columns
must be able to uniquely identify the row this is called the primary key in this example name and
address would be a potential primary key yet often the primary key is system generated in our case we
will add a computer generated primary key the primary key is of great importance and features
prominently in all other normalization rules three it also means that each column name must be unique
and in this case we need to rename our skill columns to make them unique and four there
must be no repeating groups repeating groups are removed and put into a new spreadsheet or table
now we have two spreadsheets or tables with nice rows of data it is uniquely identified
each has no more than one value in each cell and there are no repeating group yay welcome to first
normal form but the fun doesn't stop here second normal form enforces new rules and states that
all data must depend on the primary key so let's first examine spreadsheet one name and address and
job names are all related to employee id so it's already in second normal form yay that's great
but what about the second spreadsheet skill name relates to skill id but not to employee id
second normal form stipulates that any column that don't depend on the whole primary key must
be split into its own spreadsheet or table so we need to create one more called employee skill
a primary key that links to other spreadsheets or tables are also called a foreign key
so in this case employee id is the foreign key of employee and skill id is a foreign key of skill
now i have three spreadsheets or tables with nice rows of data
but each column depends on whole primary key yay again welcome to second normal form
but dr codd still wasn't happy it introduced a set of type 2 rules called third normal form
third normal form also focuses on the primary key and states that the primary key must fully define
all columns and columns might not depend on any other key so let's examine our spreadsheets again
in skills skill id defines skill name and skill name does not relate to any other key
so it's satisfied third normal form in employee skills employee id and skill id has no other
columns and hence satisfied third normal form in employee employee id defines name and address
and name and address do not relate to any other key and hence satisfied third normal form
but employee id does not define job name hence violating third normal form
this means that job name needs to be split into its own spreadsheet and table and for
consistency we have created a computer-generated job id because the job id links employee and job
we need to create a new column job id in employee as we discussed in second normal form
any primary key that links spreadsheets or tables also become a foreign key
now we have four spreadsheets or tables with nice rows of data but a primary key defines
each non-key column welcome to third normal form in summary third normal form has transformed
one unnormalized spreadsheet or table into four normalized spreadsheets
i hope this has explained normalization and how to normalize data to third normal form
and if you enjoyed this video please hit like and subscribe hope to see you in my next video
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