Week 9 Summary — May 25–30, 2026

AWS re/Start Cohort 3: Project CloudIgnite

What We Learned

Database Fundamentals (Mon May 25)

Data models: Relational (SQL), Semi-structured (CSV/XML), Entity-Relationship, Object-Based (JSON)
Relational database: Tables with rows/columns; fixed schema; primary keys and foreign keys
Relationships: One-to-One, One-to-Many, Many-to-Many
SQL categories: DDL (CREATE, ALTER, DROP), DML (INSERT, UPDATE, DELETE), DQL (SELECT), DCL (GRANT, REVOKE), TCL (COMMIT, ROLLBACK)
Data types: CHAR(n) vs VARCHAR(n), SMALLINT/INT/BIGINT, DECIMAL vs FLOAT/REAL, DATE/TIME/TIMESTAMP
Constraints: NOT NULL, UNIQUE, DEFAULT, PRIMARY KEY, FOREIGN KEY
Transactions: ACID properties (Atomicity, Consistency, Isolation, Durability)
AWS database services: RDS, Aurora (SQL), DynamoDB, DocumentDB (NoSQL)

SQL DDL & DML (Tue May 26)

DDL commands: CREATE DATABASE/TABLE, ALTER TABLE, DROP TABLE, SHOW, DESCRIBE
DML commands: INSERT INTO, SELECT, UPDATE SET, DELETE FROM
CSV import/export: LOAD DATA INFILE, SELECT INTO OUTFILE
Data cleaning: Common errors, SQL string functions (TRIM, CONCAT, UPPER, LOWER, LEFT, RIGHT)
Labs 268–269: Creating databases/tables, inserting/updating/deleting data, loading from SQL files

SQL Queries & Filtering (Thu May 28)

NULL values: Absence of value; NULL = NULL is FALSE; use IS NULL / IS NOT NULL
WHERE filtering: =, <>, >, <, AND, OR, IN, BETWEEN, LIKE
LIKE wildcards: % = zero or more chars; _ = exactly one char
GROUP BY: Groups rows for aggregate calculations; HAVING: Filters groups after GROUP BY
ORDER BY: ASC (default) / DESC; LIMIT: Cap returned rows
Lab 270: WHERE, LIKE, IN, BETWEEN, aggregate queries on world database

SQL Advanced Queries (Fri May 29)

Operator precedence: Parentheses > Arithmetic > Comparison > NOT > AND > OR
Aggregate functions: SUM(), AVG(), COUNT(), MAX(), MIN()
DISTINCT: Removes duplicate values; COUNT(DISTINCT col)
String/Date functions: LOWER, UPPER, TRIM, CHAR_LENGTH, CURRENT_DATE, DATE_ADD
Labs 271–272: Conditional queries, aggregate functions, string functions, customer table filtering

MySQL Labs (Sat May 30)

Labs 268–271: Full hands-on MySQL practice
Common mistakes: Using == instead of =, forgetting WHERE on UPDATE/DELETE, parent-child delete order

Key CLF-C02 Connections

Amazon RDS (managed relational DB), Aurora (AWS-native, high performance), DynamoDB (NoSQL), DocumentDB, Redshift
EC2 for lab environments, SSM Session Manager (secure keyless access), Security Groups
Shared Responsibility Model (self-managed DB on EC2 vs managed RDS)

Daily Notes

May 25 — Database Fundamentals, Data Models, SQL Overview, Constraints, ACID, DBaaS
May 26 — SQL Data Types, DDL & DML, CSV Import/Export, Data Cleaning
May 28 — NULL Values, SELECT Statement, WHERE/LIKE/IN/BETWEEN, GROUP BY/HAVING
May 29 — Operator Precedence, NULL Behavior, Aggregate Functions, String Functions
May 30 — MySQL Labs 268–271, Full Hands-on Practice

What We Learned

Database Fundamentals (Mon May 25)

Data models: Relational (SQL), Semi-structured (CSV/XML), Entity-Relationship, Object-Based (JSON)

Relational database: Tables with rows/columns; fixed schema; primary keys and foreign keys

Relationships: One-to-One, One-to-Many, Many-to-Many

SQL categories: DDL (CREATE, ALTER, DROP), DML (INSERT, UPDATE, DELETE), DQL (SELECT), DCL (GRANT, REVOKE), TCL (COMMIT, ROLLBACK)

Data types: CHAR(n) vs VARCHAR(n), SMALLINT/INT/BIGINT, DECIMAL vs FLOAT/REAL, DATE/TIME/TIMESTAMP

Constraints: NOT NULL, UNIQUE, DEFAULT, PRIMARY KEY, FOREIGN KEY

Transactions: ACID properties (Atomicity, Consistency, Isolation, Durability)

AWS database services: RDS, Aurora (SQL), DynamoDB, DocumentDB (NoSQL)

SQL DDL & DML (Tue May 26)

DDL commands: CREATE DATABASE/TABLE, ALTER TABLE, DROP TABLE, SHOW, DESCRIBE

DML commands: INSERT INTO, SELECT, UPDATE SET, DELETE FROM

CSV import/export: LOAD DATA INFILE, SELECT INTO OUTFILE

Data cleaning: Common errors, SQL string functions (TRIM, CONCAT, UPPER, LOWER, LEFT, RIGHT)

Labs 268–269: Creating databases/tables, inserting/updating/deleting data, loading from SQL files

SQL Queries & Filtering (Thu May 28)

NULL values: Absence of value; NULL = NULL is FALSE; use IS NULL / IS NOT NULL

WHERE filtering: =, <>, >, <, AND, OR, IN, BETWEEN, LIKE

LIKE wildcards: % = zero or more chars; _ = exactly one char

GROUP BY: Groups rows for aggregate calculations; HAVING: Filters groups after GROUP BY

ORDER BY: ASC (default) / DESC; LIMIT: Cap returned rows

Lab 270: WHERE, LIKE, IN, BETWEEN, aggregate queries on world database

SQL Advanced Queries (Fri May 29)

Operator precedence: Parentheses > Arithmetic > Comparison > NOT > AND > OR

Aggregate functions: SUM(), AVG(), COUNT(), MAX(), MIN()

DISTINCT: Removes duplicate values; COUNT(DISTINCT col)

String/Date functions: LOWER, UPPER, TRIM, CHAR_LENGTH, CURRENT_DATE, DATE_ADD

Labs 271–272: Conditional queries, aggregate functions, string functions, customer table filtering

MySQL Labs (Sat May 30)

Labs 268–271: Full hands-on MySQL practice

Common mistakes: Using == instead of =, forgetting WHERE on UPDATE/DELETE, parent-child delete order

Key CLF-C02 Connections

Amazon RDS (managed relational DB), Aurora (AWS-native, high performance), DynamoDB (NoSQL), DocumentDB, Redshift

EC2 for lab environments, SSM Session Manager (secure keyless access), Security Groups

Shared Responsibility Model (self-managed DB on EC2 vs managed RDS)

Daily Notes

May 25 — Database Fundamentals, Data Models, SQL Overview, Constraints, ACID, DBaaS

May 26 — SQL Data Types, DDL & DML, CSV Import/Export, Data Cleaning

May 28 — NULL Values, SELECT Statement, WHERE/LIKE/IN/BETWEEN, GROUP BY/HAVING

May 29 — Operator Precedence, NULL Behavior, Aggregate Functions, String Functions

May 30 — MySQL Labs 268–271, Full Hands-on Practice