Lesson 1: What is Data? The Building Blocks of Information

Accurate (Précise): Free from errors.
Relevant (Pertinente): Directly related to the task at hand.
Timely (Opportun): Available when needed and up-to-date.
Complete (Complète): All necessary pieces of information are present.

Welcome to the world of databases! Before we dive into complex systems, we must understand the core concept: Data.

Data vs. Information

In everyday language, we often use these terms interchangeably, but they have distinct meanings in computing:

Data (Les Données): Raw, unorganized facts, figures, and observations. Data has no inherent context or meaning on its own.
- Examples: 25, Maria, 1990-05-15, Apt 3B.
Information (L'Information): Data that has been processed, organized, structured, or presented within a context to make it useful.
- Examples: 'Maria is 25 years old.' or 'The patient's date of birth is 1990-05-15.'

Key Takeaway: Databases are designed to store raw data efficiently, allowing us to retrieve organized information.

When we plan to store data in a database, we aim for quality. Good data is:

Data comes in many forms, which we categorize based on its structure:

Type	Description	Example
Structured	Highly organized data that resides in fixed fields (like spreadsheets or traditional databases).	Customer names, product IDs, financial transactions.
Semi-structured	Data that doesn't fit a fixed schema but contains tags or markers to separate data elements.	JSON files, XML files, Emails.
Unstructured	Data that has no identifiable structure. It makes up the majority of modern data.	Videos, audio recordings, free-form text documents.

In this course, we will primarily focus on managing Structured Data using Relational Databases.