u/Background-Film3405

Few weeks before, I manifested that I would write codes on my own without using AI in this AI world. Sounds weird right , where people say learning a language using AI is the wise one..

I am an old-school type of guy, looking for jobs as a SQL developer.
Where, in this course of time, I have watched n number of tutorials and practiced in HackerRank,
but still I used to forget the 4 lines of code which I typed yesterday.
So, I used to reset the IDE and type the code again and read it like a parrot.

I was completely exhausted.
Then one day, I thought , right or wrong
I would stick to my plan and practice daily topic-by-topic and understand why this cosdse works for this code.

This breakdown of my work my coding journey helped me a lot:-

>SQL keywords are not case sensitive but table names are case sensitive in some database systems

>Limiting the data set size and following best practices for SQL code indentation

>Exploring unique values and understanding semicolon usage in SQL queries

>Using SQL comments and debugging techniques

>Understanding ASC and DESC sorting in SQL

>Understanding SQL comparison operators and logical operators

>Using AND and OR logical operators for conditional queries

>Practicing advanced SQL queries using conditions for job search analysis

>Using parentheses to define conditions in SQL queries

>Using wildcard operators like % and _ for flexible search queries

>Renaming columns and tables in SQL

>SQL operations for data analytics and business analysis

>Using SQL to adjust rates for analytical purposes

>Introduction to aggregation functions in SQL

>Using aggregation methods like SUM, COUNT, DISTINCT, AVG, MIN, and MAX for salary analysis

>Using the HAVING keyword for filtering aggregated SQL data

>Calculating total earnings per project using SQL

>Introduction to different types of joins in SQL

>Combining job posting fact tables with company dimension tables using LEFT JOIN

>Understanding the purpose of RIGHT JOIN and INNER JOIN

>Performing INNER JOIN operations to connect tables using job IDs

>Understanding SQL query execution order for better efficiency

>Analyzing skills and job postings data using SQL

>Using PostgreSQL with Visual Studio Code for real-world SQL interactions

>Downloading and setting up PostgreSQL for data analytics

>Setting up Visual Studio Code as the code editor for SQL queries

>Exploring SQL tools like DataGrip and DBeaver

>Installing SQL tools in VS Code for database connections

>Connecting to PostgreSQL databases and creating new databases

>Understanding SQL data types

>Using appropriate data types for efficient SQL querying

>Creating tables using SQL syntax

>Creating and verifying table connections in SQL

>Using ALTER TABLE to modify table structures and data

>Renaming and modifying column data in SQL

>Loading databases for advanced SQL analysis

>Preparing SQL files for table creation

>Understanding primary keys and foreign keys in SQL tables

>Loading data into tables using the SQL COPY command

>Handling timestamps and dates in SQL

>Converting timestamps into dates

>Extracting specific information from date columns using the EXTRACT function

>Aggregating data using SQL

>Creating tables for multiple months using SQL commands

>Creating tables using the EXTRACT function and validating results

>Creating labels for job locations and analyzing job data with SQL

>Using subqueries and Common Table Expressions (CTEs) for complex analysis

>Using subqueries to filter job postings based on degree requirements

>Using CTEs for temporary result sets in SQL

>Using LEFT JOIN to combine tables for complete data listings

>Using SQL to identify companies with the highest number of job postings

>Joining tables to correlate and filter data

>Grouping data by specific columns and removing unnecessary columns during aggregation

>Using the UNION operator to combine results from multiple SELECT statements

>Understanding UNION and UNION ALL in SQL

>Filtering job postings based on specific criteria

>Building a SQL Capstone project

>Using GitHub for version control and repository maintenance

>Setting up local and remote repositories for collaboration

>Creating repositories using VS Code and GitHub

>Managing large SQL files in GitHub

>Syncing changes between local and remote repositories

>Setting up repositories for SQL query management

>Removing null values and retrieving top 10 results with sorting and company details

>Analyzing top-paying data analyst jobs and identifying important skills

>Performing INNER JOIN operations to connect relevant analytical tables

>Organizing salary data using SQL queries

>Identifying SQL and Python as top skills for remote data analyst jobs

>Optimizing SQL queries for faster performance

>Analyzing top skills based on salary trends

>Using aggregation methods to calculate average salaries

>Exploring remote work trends and top-paying skills in data analytics

>Using CTEs to combine demand and average salary data for optimal skill analysis

>Combining data from multiple queries using INNER JOIN

>Troubleshooting SQL queries and handling query integration issues

>Understanding the value of cloud tools and cloud-based databases in job markets

>Organizing SQL files for project documentation

>Exploring top-paying jobs and demand trends in data analytics

>Analyzing highest-paying data analyst jobs

>Utilizing tables for in-depth data analysis

I frankly say this was given to me by ChatGPT. Thanks to the OpenAI Team.

I know it is too long, but I am a real example of this..
Alas, now I have used that, and the one who wrote only SELECT statements,
now he can define when to use CTEs, SubQueries and JOINS.
It's the beginning of trial and errors

>I would love it if professionals in this forum take your free time to see my GitHub link and give your opinions on what more I can do in this tech domain.