From Basics to Mastery: My Journey Learning SQL

INTRODUCTION

Have you ever wondered how businesses manage huge amounts of data efficiently? SQL, also known as Structured Query Language, is an essential language in modern data management. Simply put, it is a programming language for storing and processing information in a relational database.

Mastering SQL has become crucial for people looking to work with databases and use them efficiently. As I completed my SQL training, I wanted to share my journey. I hope this helps!

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MY JOURNEY WITH SQL

It was in my final year of B.Tech where I had a subject named SQL. This programming language sparked my interest and I realized its importance in handling and analyzing data. I began my journey with Skill Nation, which gave me solid knowledge about SQL.

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FUNDAMENTALS OF SQL

In the initial stages, I focused on learning concepts such as Data, Oracle database, Database mode, database logical view, data constraints like primary key, foreign key, unique key, not null, check, and database object lists like Tables, Views, Functions, Indexes, and so on.

I learned basic SQL commands like SELECT, CREATE, ALTER, DROP, TRUNCATE, RENAME, INSERT, UPDATE, DELETE, COMMIT, ROLLBACK, SAVE POINT, GRANT, and REVOKE. Practicing them, like creating simple databases and performing DML operations, helped me learn these concepts.

Example:

SELECT EMPLOYEE_ID FROM EMPLOYEES WHERE DEPARTMENT_ID = 80;        

DIVING DEEPER INTO SQL

As I progressed, I explored more SQL topics, learning how to work with SQL functions and JOINS. Understanding different joins allowed me to combine different relations.

Further, I learned about DBMS and its goals, and why the File Management System (FMS) was replaced with DBMS. I was amazed by the work of DBMS. I was educated about the class of Users and what happens when we query a database.

The data model, a main tool that provides data abstraction by hiding the details of data storage which is not needed by users, was fascinating. As I progressed, I learned more about schema, RDBMS, and CODD rules, as well as the ER model, constraints of the ER model, and normalization.

When going deeper into normalization, I found that we need to accept redundancies in some particular cases, which is denormalization. It was fun concatenating values in attributes.

SELECT FIRST_NAME || ‘ ‘ || LAST_NAME FROM EMPLOYEES;        

Substitution variables to query different values. This is the topic where I got to know about ORDER BY and GROUP BY clause. Single row and general functions were easy to understand.

Conditional expressions provide the use of IF_THEN_ELSE logic within a SQL statement. Till now, I have discussed the values in the database, and how about making calculations out of them? Of course, it's about group functions. It operates on a set of rows to give one result per group. This includes average, count, minimum, maximum, and so on. Further, I learned about subqueries and operators like UNION, UNION ALL, INTERSECT, and MINUS.

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ADVANCED TECHNIQUES

It is equally important to know where to add and remove tuples if the view contains what clause, keyword, and options with DML operations. Further into the advanced level, I got to know where NEXTVAL and CURRVAL can be used and where they cannot.

CACHING is something that helps to have faster access to those values in memory, and INDEX is created to improve the performance of some queries.

Next, I learned about managing schema objects, where I explored more from set unused, on delete clause to temporary tables, and external tables including drop table purge.

Drop table purge:

DROP TABLE DEPT PURGE;        

Flashback table:

FLASHBACK TABLE EMPLOYEE TO BEFORE DROP;        

Finally, I learned about data dictionary views and structure, and how to manipulate data by using subqueries, conditional and unconditional insert, scalar subquery expressions, and correlated subqueries.

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CHALLENGES FACED

Learning SQL wasn't without its challenges. One major hurdle was optimizing queries for better performance. By studying indexing strategies and analyzing execution plans, I learned how to write more efficient queries.

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TIPS FOR LEARNING SQL

PRACTICE REGULARLY: Practice is key to mastering SQL. Work on various exercises and projects to test your understanding.

I used Hackerrank and Oracle Live SQL to solve exercises regularly.

USE REAL DATA: Engage with real datasets to understand practical applications.

ONLINE RESOURCES: Utilize resources like websites, courses, and books.

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CONCLUSION

My journey in learning SQL has been challenging. I have gained a deep understanding of SQL’s power in managing and analyzing data, and I'm excited to apply these skills in real-world scenarios.