SQL is everywhere.

It’s the language behind almost every database you interact with, whether you realize it or not.

But here’s the thing.

Most people only learn enough SQL to scrape by.

A simple SELECT statement here and there.

But SQL is far more than just a query language. When used to its potential, it becomes one of the most powerful tools in your analytics toolkit. It’s capable of taking raw data and turning it into insights that drive decision making.

If you want to get serious about your data skills, SQL needs to become a priority.

Here are 6 essential steps to take you from beginner to advanced user:

• The Big Six – The core query structure

• CASE Statements – Adding if-then logic into your queries

• JOINs – Combining data across multiple tables

• Subqueries & CTEs – Breaking down complex logic into digestible parts

• Window Functions – Using advanced calculations without collapsing your data

• Data Type Functions – Cleaning and prepping your data.

Let’s break these down one by one.

1. The Big Six

These are the foundational building blocks of nearly every SQL query:

• SELECT – defines what fields to return

• FROM – defines the source tables

• WHERE – filters your rows before grouping

• GROUP BY – aggregates rows into groups

• HAVING – filters based on groupings

• ORDER BY – sorts your final result

How Does It Work?

SQL runs your queries using a logical processing order. 

This means it doesn’t execute your statements in the order you write them. Instead, SQL processes each clause in a specific sequence that affects how data is retrieved, filtered, grouped, and returned.

Here’s the actual logical processing order SQL follows:

1. FROM – SQL starts by identifying the source tables.

2. JOIN – If joins are present, they’re applied next to combine tables.

3. WHERE – Filters rows based on conditions before any grouping.

4. GROUP BY – Groups the filtered rows for aggregation.

5. HAVING – Applies filters on the aggregated results.

6. SELECT – Defines which columns and expressions are returned.

7. ORDER BY – Sorts the final output.

Looking under the hood and understanding how SQL queries execute is just a helpful thing to know.

Why The Big Six is Important

• Forms the foundation for more advanced query logic

• Teaches clean and logical query structuring

• Required knowledge for interviews and real-world analysis

2. CASE Statements

CASE statements are SQL’s version of "if this, then that." It allows you to add custom logic directly into your query results.

How Does It Work?

You write conditional expressions using the CASE WHEN … THEN … ELSE … END syntax. 

It can be used in SELECT, WHERE, or ORDER BY clauses to assign categories, flags, or conditional calculations. You can even nest multiple CASE statements or combine them with aggregations to segment your results dynamically.

Why It’s Important

• Adds flexibility to your analysis

• Enables you to categorize metrics

• Lets you replicate logic that would otherwise require multiple queries

3. JOINs

Most datasets in the real world are spread across multiple tables. JOINs let you bring them together in one query.

How Does It Work?

JOINs link rows from two or more tables based on a related column. Here are a few essential types of joins to know:

• INNER JOIN – matches only rows that exist in both tables

• LEFT JOIN – brings in all records from the left table, and matches from the right

• RIGHT JOIN – the inverse of a LEFT JOIN

• FULL OUTER JOIN – includes all rows from both sides, matched where possible

JOINs are necessary knowledge and give you flexibility when all of your data isn’t stored in one table (which is almost always the case).

Side note: Use UNION and UNION ALL to vertically stack results from separate queries with the same structure. Not a JOIN, but it's an alternative way of combining multiple tables. It works like this:

Why It’s Important

• Essential for working with relational databases

• Allows for more comprehensive, multi-dimensional analysis

• Gives you control over how data is connected and displayed

4. Subqueries & CTEs

As SQL queries get more complex, it becomes helpful to modularize your logic. 

Subqueries and Common Table Expressions (CTEs) help break large queries into more readable chunks.

How Does It Work?

A subquery is written inside another SQL query and can appear in SELECT, FROM, or WHERE clauses. It acts as a temporary result used by the main query.

A CTE uses the WITH keyword to define a named temporary result set that can be referenced throughout your query. Unlike subqueries, CTEs are often easier to read and reuse, especially in long or layered logic.

Both tools let you isolate parts of your logic, which keeps your SQL modular, readable, and easier to troubleshoot.

Why It’s Important

• Makes complex queries easier to read and debug

• Allows for step-by-step logic in a single query

• Encourages better documentation and collaboration

5. Window Functions

Window functions let you calculate metrics across rows. But unlike GROUP BY, they don’t collapse your data.

How Does It Work?

Window functions work with the OVER() clause to define a "window" or range of rows for calculations. 

Here are some common functions:

• ROW_NUMBER() - assigns a unique sequential number to each row within a partition. Useful for ranking or deduplication.

• RANK() - assigns a rank to each row within a partition, but allows for gaps in rank when there are ties.

• DENSE_RANK() - similar to RANK() but does not leave gaps between ranks.

You can use PARTITION BY inside OVER() to restart calculations by group, and ORDER BY to control the sequencing. This allows you to do things like calculate running totals, generate rankings, or compare row-by-row values.

Why It’s Important

• Perform calculations without collapsing your dataset

• Perfect for running totals, rankings, and percent changes

• Essential for trend analysis and performance comparisons

6. Data Type Functions

SQL is also helpful in prepping and cleaning data for analysis. Data type functions help you transform and standardize your results.

How Does It Work?

SQL can manipulate strings, numbers, dates, and handle nulls. 

Here are some examples:

• String functions: LENGTH, TRIM, UPPER / LOWER, CONCAT , and LIKE

• Numeric functions: Math functions like LOG or POWER and Rounding functions like ROUND and FLOOR

• Date/time functions: CURRENT_DATE, DAYOFWEEK, or DATEDIFF

• Null handling: IFNULL, COALESCE

• Type conversion: CAST, CONVERT

These functions help clean inconsistent data, convert types, and standardize inconsistent inputs. All essential for a clean output of your analysis.

Why It’s Important

• Real-world data is messy.

• Reduces errors and inconsistencies in analysis

• Prepares your data for downstream tools like Power BI or Tableau

Final Thoughts

These six steps are all practical, real-world skills that every data analyst should have in their SQL toolkit.

Practice consistently and you’ll master each of these areas.

And if you want to learn all of these concepts in a structured, hands-on way, check out one of Maven’s 10-week SQL immersive cohorts.

You’ll be guided live by our expert instructors, practice with real projects, and leave with the confidence to handle just about any SQL challenge.

The next one is starting soon. Hope to see you there.