SQL In Relational Database Management System In the Tech World

SQL, the industry Standard Query Language is used to access, manipulate, communicate with, and manage Relational Database Systems. It provides users with CRUD functionality: CREATE data in a database; READ it; UPDATE, and DELETE the data. SQL statements are used to perform actions on databases. Users query databases using SQL English-like commands such as CREATE DATABASE, DELETE, UPDATE, SELECT, INSERT INTO, CREATE TABLE, DROP TABEL, etc. Keywords in SQL are specifically written in uppercase.

SQL is the cornerstone of data processing and by extension, the modern business world. In this ever-changing world of Information Technology, most companies are investing in technology that will gather data in the most functioning and well-organized manner. This task requires professionals who possess skills such as Managing, Presenting, and Analysis of data using computer programs to transform these raw data into resourceful information which will be used for business insights. Have you observed that companies that used to provide services and products are now investing more in digital technologies that deal with large data?

First developed by IBM (International Business Machines Corporation) in the 1970s, SQL has grown in popularity and advancement over the years and it is a flexible computer language widely used for handling databases, specifically Relational Databases.

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Before delving further into SQL, let’s define a database. Although there is no strict definition to it, a database is an organized collection of data or records that can be easily accessed and managed for the purpose of gathering information. Whether it’s a school, university, or any big company, everyone uses a database. Traditional databases are stored in rows and columns. Tables and indexes are some of the attributes that make a database. In essence, this collection of data is managed and administered by a software called Database Management System (DBMS).

Categories of SQL

DQL (Data Query Language)

A Data Query Language is used to fetch data from tables based on conditions. An example is the “SELECT” command which is used to fetch or retrieve data from one table or more based on conditions.

DDL (Data Definition Language)

This is used to define the database schema. It basically deals with the description of the database schema and is used to create and adjust the structure of objects in a database such as CREATE, DROP, ALTER, RENAME, TRUNCATE, etc.
CREATE: to create a database or its objects such as tables, indexes, functions, view, store procedure, and triggers.
DROP: to remove a table or database.
ALTER: to modify the structure of an existing database. This includes adding columns or more.
RENAME: to rename an object.
TRUNCATE: to take away all records from a table.

DML (Data Manipulation Language)

This command is used for manipulating the data such as INSERT, UPDATE, and DELETE.
INSERT: used to add data into a table.
UPDATE: used to update existing data into a table.
DELETE: to remove all rows and particular rows from a table.

DCL (Data Control Language)

This is used to allow or restrict users from accessing data in a database schema. DCL commands include GRANT and REVOKE.
GRANT: this allows user’s access privileges to databases.
REVOKE: used to withdraw users’ access privileges given by using GRANT command.

TCL (Transaction Control Language)

This command deals with the databases and is used to check on other commands and their effects in the database. They include COMMIT, ROLLBACK, SAVEPOINT, etc.
COMMIT: used to permanently save data.
ROLLBACK: used to undo changes.
SAVEPOINT: use to save temporarily.

With the help of DBMS, we can take care of the following:

  • Data Security
  • Data Backup
  • Manage huge large
  • Serve multiple current database requests.

In Relational Database, we store portions of the data in designated tables and each table contains Rows and Columns. A common example is where we have Names of customers on one table, Products in another, and Orders on another table hence we split items up into tables. These tables are related based on a unique identifier known as key. Examples of RDB are Amazon AURORA, MS SQL Server, ORACLE DB, MYSQL, MariaDB, POSTGRES SQL.

Use of SQL In Relational Database Management

Gathering Metrics Using SQL

SQL can be used to gather metrics. This is one of the most common uses of SQL. Businesses define their goals with KPI (Key Performance Indicator). KPI are important facts that cannot be measured directly such as customer retention, Product usage, profit per region, and customer value. Related things that we can measure directly are called Metrics and these measurements are often stored in databases. For example, e-commerce companies collect many types of data about user’s behaviour on a site and combine measurements about them to enforce something about the customer’s relationship. Much of this analysis starts with SQL, sometimes you will be tasked with gathering metrics about a particular kind of question and you will need to carefully select relevant segments of the data using SQL.

Data Mining With SQL


Some companies collect so much data that they don’t know what to do with it so they pour it into a semi-structured data storage called a data Lake. Data mining is the process of extracting knowledge from data where it may or may not be found.

Gap Analysis

This strategic element of BI (Business Intelligence) can be defined as the process of identifying how well an organization’s outcome aligns with its expectations and what steps are necessary to improve the situation. This might involve close inspection of failure cases and look out for unusual metrics. A report based on this kind of analysis can suggest a new course of action or a new avenue for data collection.

Business Rule Analysis

This is about investigating a business’ rule of operation. Managers and executives are very interested to learn whether their goals are actually being achieved and whether their decision is having secondary side effects. Business Rules are indicators built into SQL that can help measure the health of the business’ operations.


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