80% of data problems can be solved with just 16 SQL functions.

I’ve been working with data for years and this truth keeps proving itself:

You don’t need fancy tools.
You need to master the fundamentals.

For data analysts, data scientists, and data engineers:
SQL isn’t optional.
Because data lives in databases.
And databases speak SQL-ish.

Most problems fall into 2 categories:
Aggregate functions (summarise data):

SUM() - Total revenue
COUNT() - Total orders
AVG() - Average purchase value
MIN() - Smallest sale
MAX() - Biggest transaction
STRING_AGG() - Combine text values

Window functions (compare rows):

ROW_NUMBER() - Pagination
RANK() - Leaderboards with ties
DENSE_RANK() - Performance tiers
NTILE() - Split into quartiles
LEAD() - Compare current vs next
LAG() - Compare current vs previous
FIRST_VALUE() - Highest value per group
LAST_VALUE() - Lowest value per group
SUM() OVER() - Running totals
AVG() OVER() - Moving averages

Aggregates collapse rows → one summary result
Window functions keep all rows → add calculations across them