What is SQL and best way to learn SQL for Data Science

The first question comes to our mind while study about databases is, What is SQL? In simple words, the Answer is Structured query language (SQL) is a database programming language for storing and processing information in a relational database. To store, update or modify, remove, and retrieve data from the database, we utilize SQL statements. Let’s see the best way to learn SQL for data science.

What is Data?

Data is nothing but a collection of small units of information. It can be in different forms like text, numbers, media, bytes, and so on. 

What is a database?

A database is a structured/organized collection of data that can be easily accessed and controlled.

In order to easily access relevant information, we can organize data into tables, rows, and columns, and index it.

The database’s main function is to manage a huge amount of information by storing, retrieving, and managing data. 

What are the different types of databases?

1. Hierarchical Database

2. Relational Database

3. Centralised Database

4. NoSQL Database

5. Cloud Database

6. Distributed Database

7. Object-Oriented Database

8. Network Database

These are the various types of databases that are used to store different types of data.

SQL, or Structured Query Language, is a programming language that is used to manipulate data contained in a database. 

What is SQL?

SQL stands for Structured Query Langauge. 

SQL is not a database management system, but it is a query language

SQL is a Standard language designed for accessing and manipulating data in a relational database management system(RDBMS) .

It stores and retrieves the data from relational databases like MySQL, MS Access, SQL Server, MS Access, Oracle, Sybase, Informix, Postgres, etc. 

What exactly is RDBMS?

RDBMS stands for Relational Database Management System.

RDBMS contains structured data (data stored in database objects known as tables). A table is a grouping of linked data entries that is made up of columns and rows.

What SQL can do, and its Applications

• Execute different database queries against a database.

• To Define the data in a database and to manipulate that data.

• To Create data in a relational database management system.

• To Access and Retrieve the data from the relational database management system.

• Insert, update, and delete the data from the relational database.

• Helps to describe the structured data.

• create, drop, and manipulate the tables and the database present in that tables.

• Create view, stored procedure, and functions in the relational database.

• To Define the data and modify the stored data in the relational database.

• To set permissions or constraints on table columns, views, and stored procedures.

Why Should You Study SQL?  

  • If you want to become a brilliant software engineer, especially if you work in the software development domain, or if you are just starting to study any programming language, it is highly recommended that you learn SQL. 
  • SQL is the most widely used language in practically every application program, including banking, finance, education, and security, to store and modify data.
  • SQL is fairly simple to learn, and there are numerous advantages that make SQL the first choice of any programmer. 

How SQL is used in data analytics and the best way to learn SQL for data science

An in-depth knowledge of SQL (Structured Query Language) is not only essential in the rapidly changing field of data analysis; it is an absolute must-have skill. With the help of SQL, we can do retrieval, processing, and analysis of big data, making it crucial for data analysts and professionals in a variety of industries.

How much SQL is needed for Data Analyst?

Every Data analyst must have a better understanding of SQL. SQL queries help analysts easily extract specific information. A well-knowledge of SQL allows them to work with multiple datasets, join tables, and so they can verify data accuracy. While other skills such as statistics and visualization are also useful but SQL remains a main component of efficient data analysis, as it allows analysts to extract relevant insights so that they can contribute significantly to better business decisions.

How to Master SQL: A Step-by-Step Guide

Becoming proficient in SQL requires dedication and practice. Here’s a step-by-step guide to mastering SQL:

1. Learn the Fundamentals: Start by understanding the basic SQL concepts, including SELECT statements, filtering data with WHERE clauses, and sorting results using ORDER BY.

2.  Joins and Unions: Learn how to combine data from multiple tables using joins and unions. Practice different join types to handle complex data relationships effectively.

3. Aggregate Functions: Familiarize yourself with aggregate functions like SUM, COUNT, AVG, MIN, and MAX. Practice using them to summarize and analyze data.

4. Subqueries and Nested Queries: Explore subqueries and nested queries to break down complex problems into smaller, manageable parts.

5. Database Design: Study the principles of database design to create efficient and well-structured databases.

6. Indexing and Optimization: Understand indexing techniques to enhance query performance and optimize data retrieval.

7. Real-world Projects: Work on real-world projects to apply your SQL skills and gain practical experience

Future Scope for a Data Scientist with SQL Skills 

In today’s fast-changing technological world,  we know the work of a data scientist is becoming increasingly important across businesses.  Nowadays, Data scientists are modern-day detectives, exploring important insights from huge amounts of data to make sound decisions. There are many skills that a data scientist should have, among them SQL (Structured Query Language) comes out as a foundation that has the ability to open the door to many future job opportunities. 


How long does it take to learn SQL to analyze data? 

SQL basics can be learned in a few months, but you have to invest at least 5-6 months of practice and application.

Can I use SQL to analyze big data?

Yes, SQL may be used for big data analysis, even though for large datasets, specialist tools such as Hadoop and Spark are frequently used.

How useful are SQL certifications for data analysts? 

SQL certifications can show potential employers your knowledge, but real skills and projects are equally important.

Which SQL certification is best for a data analyst or data scientist?

Following 4 SQL Certifications for Your Data Analyst Career Path:
Oracle Database SQL Certified Associate Certification
Oracle Certified Professional, MySQL 5.7 Database Administrator Certification
Microsoft Certified: Azure Data Fundamentals
EDB PostgreSQL 12 Associate Certification

What is the difference between SQL for data analysis and SQL for database administration? 

SQL for data analysis is concerned with extracting insights, whereas SQL for database management is concerned with operations such as developing, updating, and managing databases.

Does SQL have to be the only language used for data analysis? 

No, SQL is not only the language. There are other programming and database languages as well, data analysts may benefit from learning programming languages such as Python and R for more advanced data analysis.

Is SQL a must-have skill for data analysts?

SQL is an essential ability for data analysts since it allows for efficient data extraction and processing.

Is it possible to learn SQL by self-study?

Yes, there are many online tools and courses available for self-paced SQL instruction. W3Scool, OpenAI platforms are open-source, and you can practice online and learn from it.

What advanced SQL approaches are there?

Subqueries, window functions, and stored procedures are some advanced data manipulation techniques.

What is the significance of query optimization?

Query optimization improves performance by allowing for faster data retrieval and analysis.

How to keep updated with SQL trends?

To stay updated, participate in online networks, attend workshops, and read industry publications.

What is the role of SQL in data science?

SQL is essential in data science because it allows for data extraction, transformation, and analysis from databases.

Which industries value data scientists with SQL skills?

Data scientists who can work with SQL are in high demand in industries such as banking, healthcare, e-commerce, and manufacturing. Today, data scientists and data engineers are required in almost every field.

How can I improve my SQL abilities as a data scientist?

You may improve your SQL skills by attending online classes, engaging in projects, and also you can practice real-world data manipulation. w3schools, openAI-like platforms will be a good source in the long term.

What is the average salary for a data scientist with SQL skills in World?

The average salary for Data Scientist is $1,52,253 per year in the United States, as per Glassdoor analysis.
The average additional cash compensation for a Data Scientist in the United States is $34,607, with a range from $25,955 – $48,450.

What is the average salary for a data scientist with SQL skills in India?

The average salary for Data Scientist is ₹13,80,275 per year in India, as per Glassdoor analysis. The average additional cash compensation for a Data Scientist in India is ₹1,50,000, with a range from ₹80,000 – ₹2,00,000.

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