Data science has earned the reputation of being the most promising job of the times, even during this pandemic crisis. With the current changes in the global business and economic background, data science has proven to be a more relevant career opportunity. If you are following the subject and have a keen interest in making a data science career choice, you must have heard about SQL as well.
SQL is used to access and manipulate data. It helps to store data, access whenever you need it, and retrieve if need be. SQL training will give you a much-required head start in the highly competitive job market.
Why is SQL Important in Data Science?
Today’s business decisions are data-driven. Data is generated all through the day, across the globe. The amount of data generated every day is simply astonishing – about 2.5 quintillion bytes. This underlines the enormity of the subject we are dealing with.
Now that data is available, what is the next thing? How are you going to make sense of this huge amount of data and use it to make a decision? Data science steps in here. You need to collect, organize, and process them to make sense of the data and to derive insights. To do this, you need tools. This is what SQL does. It is a querying language used to store, access, and retrieve data.
What is Structured Query Language (SQL)
SQL is a language that is primarily concerned with managing relational databases. SQL is the typical API for such data tables. While using SQL, data can be accessed and managed without changing the databases. You can perform a variety of actions including updating, querying, deleting, and inserting data records. Oracle, MySQL etc. are examples of such databases which use SQL.
SQL works based on some simple commands that are associated with different data tasks. These commands can be used to create database and tables, insert, delete, or update data, to alter table and database, drop table and index.
How to Create a Table Using SQL
Let’s see how to create a table using SQL commands. Remember to use UPPERCASE letters for SQL commands, and use semicolons to terminate commands.
You may follow the steps given below to create a database.
Step #1 Creating a Database using SQL
CREATE DATABASE: Use this command to create a database “Test”.
USE: This command activates the database.
Your database named test is ready and activated.
Step #2: Creating a Data Table
It is as easy as typing a command to create a table, just like the way you created the database. All you need to do is to decide on the variables you want to include in the table.
Suppose you want to create a table with the following features:
- Serial Number (SL)
- Purchase item
- Number of pieces
You can use the command CREATE TABLE to create the table. The four features of the table are SL, purchase item, cost, and number of pieces.
Now, to create the table, use the command as given below:
CREATE TABLE cart (SL NOT NULL PRIMARY KEY AUTO_INCREMENT Purchase_item TEXT, Cost INTEGER, Number_of_pieces INTEGER);
You might have noticed that we have given the value we are going to provide for each feature. The Serial Number is a primary key, which means it represents a unique data. The purchase item will be entered as text, while cost and number of pieces will be entered as numbers.
The table is now ready with the field names and the value to be entered to each cell of the table. To see how the table is executed, type the command “DESCRIBE cart”. This will give you a display of a table with the given features.
|Number of pieces||Int(11)||YES||NULL|
Step #3: Data Input
Once you create the table, you need to enter data into the respective fields. To do this. Use the SQL command “INSERT INTO”.
To insert values, follow this pattern:
INSERT INTO cart VALUES (NULL, “Rice”, 75, 10)
The “null” value is assigned to SL, as it will follow the command and auto_increment from 1.
The entered value will look like:
|SL||Purchase item||Cost||Number of pieces|
Follow the same pattern to enter more values.
Data Science is trending these days. Getting trained in a skill that is much in demand improves your chances of getting hired manifold.
So, choose a good data science course and give your profile an extra edge while competing for career opportunities.