Lesson Content

1) What is data?

Data is raw facts — numbers, words, pictures, clicks, or measurements. Data becomes useful when we organize it.

2) Structured vs unstructured data

Structured data fits a predictable format (often tables), making it easy to search and sort.
Unstructured data is not neatly arranged in rows/columns (photos, videos, PDFs, emails).

• Structured: bank transactions, inventory lists, class rosters
• Unstructured: selfies, YouTube videos, scanned documents

3) What is a database?

A database is an organized collection of data used by stores, schools, hospitals, banks, and apps.

4) Tables, rows, columns

• Table: a collection of related data (like a spreadsheet)
• Row (record): one item/person/order
• Column (field): one type of data (Name, Email, Age)

5) Primary key

A primary key uniquely identifies a row (examples: Order ID, Student ID, Ticket #).

6) What is SQL?

SQL helps you query and manage data in a database (read/add/change/remove records).

• SELECT (read)
• INSERT (add)
• UPDATE (change)
• DELETE (remove)

7) Database vs storage

Diagram: How data moves through a system

Figure 1: User → Application → Database → Storage, then a response returns to the user.

8) Data protection (ties to Lesson 6)

• Backups help you recover after ransomware, deletion, or drive failure
• Access controls prevent unauthorized viewing/editing
• Updates patch vulnerabilities that could expose data

9) Common database types (ITF+ friendly)

Databases come in different “styles.” The big split is relational vs non-relational.

• Relational (SQL): data stored in tables with relationships (great for structured data).
• NoSQL: flexible formats (often easier for mixed / semi-structured data at huge scale).

10) Why “normalization” exists (simple version)

Normalization is organizing tables to reduce duplicates and mistakes. Instead of repeating the same customer info in every order, you store the customer once and reference them.

• Benefit: fewer errors + easier updates
• Tradeoff: data is spread across more tables, so queries can be more complex

11) Data integrity & constraints

Databases enforce rules so data stays accurate.

• NOT NULL: this field must have a value
• UNIQUE: no duplicates (like usernames)
• Primary key: unique identifier for each row
• Foreign key: points to a row in another table (creates relationships)

12) Backup & restore basics (database angle)

Backups can be for files and also for databases. A database backup usually captures the data in a consistent way so you can restore it later.

• Full backup: everything
• Incremental: changes since last backup
• Restore: bring data back after accidental deletion, corruption, ransomware, or hardware failure

13) Quick recap

• Structured = predictable fields (tables)
• Unstructured = files/media/text blobs
• Database = organized system; storage = where bits live
• SQL = language to query/manage relational databases