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  • Before the Advent of Database Systems
    Course Introduction
    Course Syllabus
    Announcements
    Unit 1: Introduction to Modern Database Systems
    1.1: Characteristics of Databases
    Before the Advent of Database Systems
    Fundamental Concepts and Benefits of a Database
    Introduction to Database Systems
    1.2: Database Environments
    Database Models
    Types of Data Models and Data Modeling
    Elements of Database Systems
    1.3: Classifying Database Management Systems
    Classification of Database Management Systems
    Comparison of NoSQL Database Management Systems and Models
    Classifying Database Management Systems: Regular and NoSQL
    Unit 1 Assessment
    Unit 1 Assessment
    Unit 2: Database Architecture and Date Languages
    2.1: Databases and the Three-Schema Architecture
    Three-Schema Architecture
    Data Modeling and a Framework for Database System Design
    2.2: Tables, Views, and Indexes
    The Relational Data Model
    Relational Databases
    Introduction to Relational Databases
    Unit 2 Assessment
    Unit 2 Assessment
    Unit 3: The History of Databases
    3.1: Before Computers
    A Brief History of Databases
    History of Databases
    3.2: The Four Revelations
    Database Models
    Unit 3 Assessment
    Unit 3 Assessment
    Unit 4: The Entity-Relationship Model
    4.1: Why Use an E-R Model?
    Conceptual Designs
    4.2: E-R Elements and Symbols
    The Entity-Relationship Data Model
    Entity-Relationships
    Data Modeling: Entity-Relationship (E-R)
    Data Models
    Introduction to the Entity-Relationship Model
    4.3: The Enhanced E-R Model
    The Enhanced Entity-Relationship Model
    Advanced Topics in E-R Modeling
    Unit 4 Assessment
    Unit 4 Assessment
    Unit 5: The Relational Database Model
    5.1: The Relational Model at a Glance
    The Relational Data Model
    The Relational Database Model
    5.2: Mapping an E-R Diagram to a Relation
    ER Model to Relational Mapping
    Integrity Rules and Constraints
    Unit 5 Assessment
    Unit 5 Assessment
    Unit 6: Relational Algebra
    6.1: Basic Operations
    Relational Algebra
    The Relational Database Model
    Relational Algebra
    6.2: Derived Operations
    Relational Algebra and Relational Calculus
    SQL Data Manipulation Language
    6.3: Set Operations
    The Relational Database Model
    6.4: Aggregate Functions
    The Structured Query Language
    Unit 6 Assessment
    Unit 6 Assessment
    Unit 7: Introduction to Data Normalization
    7.1: Defining Normalization
    Database Normalization
    Normalization
    Normalized Database Design
    Entity Relationship Diagrams
    7.2: Anomalies
    Data Anomalies
    7.3: Functional Dependencies
    Functional Dependencies
    7.4: From 1NF to BCNF
    Normalizing a Relation to BCNF Based on Functional Dependencies
    Unit 7 Assessment
    Unit 7 Assessment
    Unit 8: Introduction to SQL
    8.1: What is SQL?
    Introduction to SQL
    Another Introduction to SQL
    8.2: Data Definition Language (DDL)
    SQL Structured Query Language
    SQL Tutorial
    Drop Table
    Alter Table
    8.3: Column- and Table-Level Constraints
    SQL Tutorial
    8.4: Data Manipulation Language (DML)
    SQL Tutorial
    SQL Insert, Update, and Delete Commands
    Unit 8 Assessment
    Unit 8 Assessment
    Unit 9: Basic Select Statements
    9.1: Basic Select Statements
    SQL Tutorial
    PostgreSQL Tutorial: AND, OR, NOT
    9.2: Special Operators
    SQL LIKE Operator
    SQL BETWEEN Operator
    SQL: Using WHERE Clause with NOT LIKE Operator and Escape Character
    MySQL SELECT Statement
    Select (SQL)
    SQL ORDER BY Clause
    Unit 9 Assessment
    Unit 9 Assessment
    Unit 10: The Join Statement
    10.1: Introduction
    INNER JOIN
    SQL Data Manipulation Language
    SQL JOINS
    Aggregates and JOINs
    10.2: Inner Joins
    Inner vs. Outer Joins in SQL
    SQL INNER JOIN
    10.3: Outer Joins
    SQL OUTER JOIN
    SQL RIGHT JOIN
    SQL Full Outer Join
    10.4: The Group By Clause
    GROUP BY
    SQL GROUP BY Clause
    10.5: Assessment
    SQL Exercises
    Unit 10 Assessment
    Unit 10 Assessment
    Study Guide
    CS403 Study Guide
    Course Feedback Survey
    Course Feedback Survey
    Certificate Final Exam
    CS403: Certificate Final Exam
    Archived Materials
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  1. CS403: Introduction to Modern Database Systems
  2. Unit 1: Introduction to Modern Database Systems
  3. 1.1: Characteristics of Databases
  4. Before the Advent of Database Systems

Before the Advent of Database Systems

Completion requirements

Read chapter 1, which begins by discussing fundamental data concepts. The study of databases is an extension of the study of data in programming. The study of databases as a discipline was motivated by a variety of factors: the increasing size and complexity of software systems, the need to share data, and the need to be able to maintain and secure data effectively.

Data is a collection of symbols used to represent numbers, text, pictures, videos, audio, and so on. How this data is represented gives the meaning (or semantics) for the symbols. Additional semantics are provided by the relationships that data has with other data. In programming, the semantics of data is provided by program documentation, as well as the programming language used to create the program. In databases, the semantics of the data is provided by a data model, which includes the representation of the data, relationships among the data, and metadata (which is data that defines other data).

Semantics makes data useful, and we define useful data as information. Sometimes, the terms 'data' and 'information' appear as synonyms. However, they are different: all information is data, but not all data is information. The type and amount of semantics determines the usefulness of some given data. Usefulness is also relative to a given user. Data may not be useful to some users, but very useful to others.

Identifying data and information and organizing them into a data model typically occurs in software requirements analysis and design. Current work in the field of databases addresses techniques that support building and storing data models, and using them to discover meaning (or information) in large volumes of data.

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Saylor Academy © 2010-2025 except as otherwise noted. Excluding course final exams, content authored by Saylor Academy is available under a Creative Commons Attribution 3.0 Unported license. Third-party materials are the copyright of their respective owners and shared under various licenses. See detailed licensing information. Saylor Academy®, Saylor.org®, and Harnessing Technology to Make Education Free® are trade names of the Constitution Foundation, a 501(c)(3) organization through which our educational activities are conducted.