🗃️ MemoLearning SQL for Data Analysis

Master database querying and data manipulation for comprehensive data analysis

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SQL for Data Analysis Curriculum

12
Core Units
~100
SQL Techniques
50+
Query Examples
8+
Database Systems
1

SQL Fundamentals

Learn the basics of SQL, database concepts, and how to write your first queries.

  • Introduction to databases
  • Relational database concepts
  • SQL syntax and structure
  • Data types and constraints
  • Tables, rows, and columns
  • Primary and foreign keys
  • Database design principles
  • SQL standards and dialects
2

Basic SELECT Queries

Master the SELECT statement to retrieve data from single tables with filtering and sorting.

  • SELECT statement syntax
  • Selecting specific columns
  • WHERE clause filtering
  • Comparison operators
  • Logical operators (AND, OR, NOT)
  • IN, BETWEEN, and LIKE operators
  • ORDER BY for sorting
  • LIMIT and TOP clauses
3

Data Manipulation

Learn to insert, update, and delete data using SQL's data manipulation language (DML).

  • INSERT statements
  • UPDATE statements
  • DELETE statements
  • INSERT with SELECT
  • Bulk operations
  • Transaction control
  • COMMIT and ROLLBACK
  • Data integrity considerations
4

Aggregate Functions

Use aggregate functions to perform calculations and summarize data across multiple rows.

  • COUNT function
  • SUM and AVG functions
  • MIN and MAX functions
  • GROUP BY clause
  • HAVING clause
  • NULL handling in aggregates
  • DISTINCT in aggregates
  • Multiple grouping levels
5

Table Joins

Combine data from multiple tables using various types of joins for comprehensive analysis.

  • Inner joins
  • Left and right outer joins
  • Full outer joins
  • Cross joins
  • Self joins
  • Multiple table joins
  • Join conditions and performance
  • Anti joins and semi joins
6

Subqueries and CTEs

Write complex queries using subqueries and Common Table Expressions for advanced data analysis.

  • Correlated subqueries
  • Non-correlated subqueries
  • EXISTS and NOT EXISTS
  • Subqueries in SELECT, FROM, WHERE
  • Common Table Expressions (CTEs)
  • Recursive CTEs
  • Multiple CTEs
  • Performance considerations
7

Window Functions

Master window functions for advanced analytics including ranking, running totals, and moving averages.

  • Window function syntax
  • OVER clause and partitioning
  • ROW_NUMBER, RANK, DENSE_RANK
  • LAG and LEAD functions
  • FIRST_VALUE and LAST_VALUE
  • Running totals and averages
  • Percentiles and NTILE
  • Frame specifications
8

Date and Time Analysis

Work with temporal data using date/time functions for time-based analysis and reporting.

  • Date and time data types
  • Date formatting and parsing
  • Date arithmetic
  • EXTRACT and DATE_PART functions
  • Time zone handling
  • Date ranges and intervals
  • Time series analysis
  • Calendar calculations
9

String Manipulation

Process and analyze text data using SQL's string functions and pattern matching.

  • String concatenation
  • SUBSTRING and string extraction
  • UPPER, LOWER, and TRIM functions
  • String length and position
  • Pattern matching with LIKE
  • Regular expressions
  • String replacement
  • Text parsing techniques
10

Advanced Analytics

Perform sophisticated analytical operations including statistical functions and data mining techniques.

  • Statistical aggregate functions
  • Correlation and covariance
  • Linear regression functions
  • Percentile calculations
  • Data binning and bucketing
  • Pivot and unpivot operations
  • Time series functions
  • Analytical use cases
11

Query Optimization

Optimize SQL queries for better performance and understand execution plans and indexing strategies.

  • Query execution plans
  • Index types and strategies
  • Query performance tuning
  • Statistics and cardinality
  • Join optimization
  • Subquery optimization
  • Partitioning strategies
  • Best practices
12

Real-world Projects

Apply SQL skills to comprehensive data analysis projects using real datasets and business scenarios.

  • Sales analysis project
  • Customer segmentation
  • Financial reporting
  • Web analytics
  • Inventory management
  • Cohort analysis
  • A/B testing analysis
  • Dashboard data preparation

Unit 1: SQL Fundamentals

Learn the basics of SQL, database concepts, and how to write your first queries.

Introduction to Databases

Understand what databases are, why they're important, and how they organize and store data efficiently.

RDBMS ACID Normalization
A database is an organized collection of structured information stored electronically in a computer system, managed by a Database Management System (DBMS).

Relational Database Concepts

Learn about tables, relationships, and how relational databases organize data into structured formats.

-- Relational database structure
Tables → Rows (Records) → Columns (Fields)
Relationships → Primary Keys → Foreign Keys

SQL Syntax and Structure

Master the basic syntax rules and structure of SQL statements for effective database communication.

SELECT column1, column2
FROM table_name
WHERE condition
ORDER BY column1;

Data Types and Constraints

Understand different data types available in SQL and how constraints ensure data integrity.

VARCHAR INTEGER DATE BOOLEAN
-- Common data types
VARCHAR(50) -- Text data
INTEGER -- Whole numbers
DATE -- Date values
DECIMAL(10,2) -- Decimal numbers

Tables, Rows, and Columns

Learn the fundamental structure of relational databases and how data is organized in a tabular format.

Table: A collection of related data entries
Row (Record): A single data entry in the table
Column (Field): A single attribute of the data

Primary and Foreign Keys

Understand how keys create relationships between tables and ensure data integrity across the database.

-- Primary Key: Unique identifier
customer_id INTEGER PRIMARY KEY

-- Foreign Key: References another table
customer_id INTEGER REFERENCES customers(id)

Database Design Principles

Learn fundamental principles of good database design including normalization and entity-relationship modeling.

1NF 2NF 3NF ER Diagram
Good database design eliminates data redundancy, ensures data integrity, and optimizes for query performance.

SQL Standards and Dialects

Explore different SQL implementations and understand the differences between various database systems.

-- SQL Standards
ANSI SQL (SQL-92, SQL:1999, SQL:2003)

-- Popular Dialects
MySQL, PostgreSQL, SQL Server, Oracle

Unit 2: Basic SELECT Queries

Master the SELECT statement to retrieve data from single tables with filtering and sorting.

SELECT Statement Syntax

Learn the fundamental structure of SELECT queries and how to retrieve data from database tables.

SELECT * FROM employees;

SELECT first_name, last_name, salary
FROM employees;

Selecting Specific Columns

Choose specific columns to retrieve and use aliases to rename columns in the result set.

SELECT
  first_name AS 'First Name',
  last_name AS 'Last Name',
  salary * 12 AS 'Annual Salary'
FROM employees;

WHERE Clause Filtering

Filter rows based on specific conditions to retrieve only the data that meets your criteria.

SELECT *
FROM employees
WHERE salary > 50000;

Comparison Operators

Use comparison operators to create conditions for filtering data effectively.

= != > < >= <=
WHERE age >= 25