Data analysis is one of the fastest-growing fields, and organizations that deal with data are constantly looking for skilled SQL professionals to retrieve their data and perform decision-making analyses on them. To be relevant in this on-demand, as a data analyst, you need to have a solid background in the basics of SQL. This article will examine the basic skills of extracting data from a database as an analyst. We focus on the fundamentals, not coding, but all theory. We will be looking at.

• What is SQL, and why do we need it?
• What is a database? 
• What is Normalization?
• Rules that guide you when writing SQL codes
• Conclusion

What is SQL, and why do we need it?

SQL is a programming language used to communicate with relational databases to fetch data from storage locations like a relational database. A relational database is a database that stores data in rows and columns (Table). SQL is a straightforward language compared to other programming languages like C++, C#, Java, etc. SQL is beneficial for data management, data manipulation, and data security. With SQL, we can manage a large amount of data by retrieving, updating, and storing it in a relational database. Also, we can use SQL for data manipulation, allowing users to sort, aggregate, and perform decision-making analysis. Finally, we need SQL because we can protect sensitive data by ensuring that only authorized personnel have access to the data through the use of user authentication.

What is a database?

A database can be seen as a storage location. It is like a container that holds objects like tables, views, stored procedures, and more. The database comes with the setup of an SQL server instance, meaning that when you provision your SQL server instance, you will be given the privilege to create a database. When working with a database, there are a few things that you need to be familiar with.

Database Schema: The schema is the guide for how data in a database are organized and structured, including the table and column data types. As an analyst, you should understand the schema of your database because it is the framework for how the data you are trying to query are stored.

Query Efficiency: As you write your SQL code, you should understand the types of joins you use to connect multiple tables. Every line of code you write in a database impacts the table; therefore, understanding queries like filtering, sorting, aggregating, etc., is crucial in writing efficient and production-ready code.

What is Normalization?

Database normalization organizes data to reduce redundancy and anomalies and improve data integrity. With normalization, any changes to data will not cause issues, and there will be no duplicated data. For a database to be in the right state, it must meet the proper normal form. A normal is the process needed to satisfy normalization. There are up to six normal forms, but we are encouraged, for the sake of best practices, to only go up to the 3NF.

Rules that guide you when writing SQL codes

 When writing your SQL codes, you must keep two things in mind. You need to understand the logical process, which is how SQL executes the code, and the next thing that you need to keep in mind is the syntactical code. The syntax is how we write the code and for humans to understand. Now, let’s break this down.

Syntactically:

• SELECT
• FROM
• WHERE
• GROUP BY
• HAVING
• ORDER BY

1. SELECT: The select is used to display the columns and rows that are specified 

2. FROM: The from clause is used to call the table or view where the data reside

3. WHERE: Where clause is used to filter rows of data that meet the specified condition

4. GROUP BY: The group by clause is used to group records that are similar

5. HAVING: The having clause is used to filter grouped records that are similar

6. ORDER BY: The order by is used to sort the records in ascending or descending.

Note: Depending on your work, you may not need all these clauses in one code block at a time. That is why it is important to understand the requirements for your project and use the clauses required to get the data.

Logical Process:

• FROM
• WHERE
• GROUP BY
• HAVING
• SELECT
• ORDER BY

1. FROM: SQL first looks at the table where the data is stored.

2. WHERE: Then SQL filters the row according to the specified conditions

3. GROUP BY: Next, SQL will group the record that is left from the filtering

4. HAVING: Then SQL filters the grouped records

5. SELECT: Then SQL returns the returns columns that are needed

Note: The difference between the WHERE and HAVING is that the WHERE is used to filter data per row while the HAVING is used to filter data that are already grouped.

Conclusion

This article discusses the basics of SQL, its importance, and how data professionals can extract data from a database for in-depth analysis. Whenever we write our SQL code, we need to consider two concepts: syntactical code and logical processing.

The next article will discuss writing various SQL codes to retrieve data and perform basic analysis. Stay tuned.