Gain insights into SQL and database fundamentals. Delve into data manipulation, administration, and normalization with practical tasks using SQL functions for backup, recovery, and user management.

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SQL is a must-know language for all types of roles, including development and data science. This course includes hands-on experience with the fundamentals of the SQL Server database including database administration.

The course covers the fundamentals of relational databases and database normalization. It offers a practical learning experience of retrieval, definition, manipulation, presentation and transformation of data through SQL functions. You will also learn database administration for backup, recovery and restore followed by managing the users, roles and privileges.

This course will teach you how to perform tasks related to SQL Server databases with hands-on experience. It covers the complete range of day-to-day operations.

A Practical Guide to SQL  and Database Fundamentals

**Normalization** is a process that Robert Boyce and Edgar Codd created back in the 1970s to optimize a database as much as possible. Each step of the normalization process has a form, which ranges from one to five, where five is the highest normal form.

By standard practice, every database must go through the normalization process.

We can implement up to the third normal form in most databases without negatively impacting functionality.


The main goal is to maintain the following:
- Integrity of data 
- Optimize the database’s efficiency 
- Provide a more efficient method of tracking  
- Storing data
- Avoid any data issues
# Data anomalies
Speaking of avoiding data issues, there are some points to be aware of, like **data anomalies**, which can create data issues in the database if we do not apply the normal forms to data. There are three types of anomalies: 

- Insert anomaly 
- Update anomaly 
- Delete anomaly 

We’ll use the table below to explain anomalies.








Supplier Table

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## Insert anomaly
The **insert anomaly** occurs when we cannot add a new record unless other attributes exist already. For instance, a company wants to sell a new product but doesn’t have a supplier yet. We’d have to wait for a valid supplier to enter here instead of just adding product information.


## Update anomaly
The update anomaly occurs when there is a need to change many values in multiple places rather than being changed in only one place. For example, if the supplier changes their name, like “Friendly Supplements, Co.,” then we have to update that in every row where it exists.

## Delete anomaly
The **delete anomaly** occurs when there’s data that we’d like to remove, but in removing it, we’d have to remove other values that we’d like to keep.

Let’s say the company no longer sells energy drinks, so we need to delete this row. This will also delete all the other values (all entries containing the supplier of energy drinks). But perhaps we want to know who supplied that product initially to keep track of the supplier’s information.

Now that we’re aware of data anomalies and how they can create issues, let’s move to the first step in normalization.


Learn about database normalization to maintain the integrity of the data, introduce flexibility, and remove inconsistency in the data.

Introduction

Database Components

Structuring the Database

Data Retrieval

Data Definition

Data Manipulation

Transforming Data and Functions

Database Administration

Conclusion

Appendix

Introducing Database Normalization

Data anomalies