Overview
The Introduction to Database Concepts lab provides you with the instruction and server hardware to develop your hands-on skills in the defined topics. This module includes the following exercises:
Learning Outcomes:
In this module, you will complete the following exercises:
- Exercise 1 - Relational Database Concepts
- Exercise 2 - Working with Data Manipulation Statements
- Exercise 3 - Working with Data Definition Language
After completing this lab, you will be able to:
- Create a table and establish table relationships.
- Use data manipulation statements.
- Use data definition language.
Key terms and descriptions
Data
Raw, unprocessed facts and figures without context (e.g., numbers, dates, strings)
Information
Data that has been processed and contextualized to be meaningful and useful
Critical data
Information essential for operations or legal compliance, such as financial records or patient health data
Non-critical data
Data that enhances user experience but is not vital for operations, such as theme settings or screen preferences
Data analytics
The process of analyzing data to extract insights for decision making
Big data
Extremely large data sets that require advanced tools and technologies (e.g., Hadoop, Spark) to process and analyze
Database
An organized collection of structured information or data, typically stored electronically and managed by a database management system (DBMS)
Flat file
A plain text or spreadsheet file where data is stored in a two-dimensional structure without relationships between records
Query
A request for data or information from a database using a specific syntax, such as SQL
Table
A database structure that organizes data into rows and columns
Row (record)
A single entry in a database table that represents one instance of data
Column (field)
A specific attribute or category of data within a table
Primary key
A column (or combination of columns) that uniquely identifies each record in a table
Foreign key
A field in one table that links to the primary key in another table, establishing a relationship between the two
Constraint
Rules applied to fields in a database to ensure data integrity (e.g., NOT NULL, UNIQUE)
Schema
The structure of a database, including tables, fields, data types, and relationships
Structured data
Data that resides in fixed fields within a record or file, often stored in relational databases
Semi-structured data
Data that does not follow a strict schema but has some organizational properties (e.g., JSON, XML)
Unstructured data
Data with no predefined format, such as videos, images, and audio files
Relational database
A type of database that stores data in tables with predefined relationships, using SQL
Non-relational database (NoSQL)
A flexible database that stores data in various formats (document, key-value, column) without requiring fixed schemas
Key-value store
A flexible database that stores data in various formats (document, key-value, column) without requiring fixed schemas
Document store
A NoSQL database that stores data as documents, often in JSON or BSON format (e.g., MongoDB)
DDL (Data Definition Language)
SQL commands that define or alter the structure of a database (e.g., CREATE, ALTER, DROP)
DML (Data Manipulation Language)
SQL commands used to manipulate data within tables (e.g., INSERT, SELECT, UPDATE, DELETE)