INFO MANAGEMENT MIDTERMS

Data

• Raw facts that are collected, stored, and analyzed.

• is the smallest unit of factual information.

• is unprocessed

Information

• Processed data that has been given context, making it useful for decision-making.

• is data that has been interpreted and analyzed.

database

• is a structured collection of data organized to facilitate efficient storage, retrieval, and management of information.

• are used in business, research, administration, and many other areas.

• To manage large volumes of data efficiently by providing centralized storage, ensuring data consistency, and enabling easy access.

• Distributed Database

• Relational Database

• Object-Oriented Database

• Centralized Database

• Cloud Database

DROCC

Types of Databases

Distributed Database

Data is distributed across different locations.

Relational Database

• Stores data in tables and is managed by a Relational Database Management System (RDBMS).

• organizes data into tables (relations) with rows and columns.

Object-Oriented Database

Supports storing all data types in the form of objects.

Centralized Database

Data is stored in a single central location

Cloud Database

Designed for virtualized environments, offering scalability and high availability.

Database Management System (DBMS)

 A collection of programs that allow users to create, manipulate, and manage databases.

Database Architecture

refers to the design of the DBMS.

• One-Tier Architecture

• Two-Tier Architecture

• Three-Tier Architecture

Types of DBMS Architecture

One-Tier Architecture

Direct interaction with the database.

Two-Tier Architecture

Client-server model.

Three-Tier Architecture

Adds a middle layer (application server) between the client and the database.

Data modeling

is the process of defining and organizing data requirements for a system or application.

Entities

Real-world objects or concepts with data stored about them.

Attributes

Characteristics of entities.

Relationship

• Connections between entities.

• refers to how tables in a relational database are linked using keys.

Primary Key

Unique identifier for a record

Foreign Key

Links tables by referencing a primary key in another table.

• Conceptual Data Model

• Representational Data Model

• Physical Data Model

CRP

Types of Data Models

Conceptual Data Model

• Represents the database at a high level.

• Focuses on business needs and is used during requirement gathering.

• Represents data in real-world terms, ignoring hardware and software constraints.

Representational Data Model

• Adds logical structure to the conceptual model.

Physical Data Model

• Describes how data will be stored in a specific database system.

• Specifies attributes' data types, lengths, indexes, and constraints.

Business rules

are specifications describing business logic, policies, and procedures.

• Hierarchical Model

• Network Model

• Relational Model

• Entity-Relationship (ER) Model

• Object-Oriented Model

• NoSQL Models

  HENRON

Evolution of Data Models

Hierarchical Model

Tree-like structure for one-to-many relationships.

Network Model

Graph structure allowing many-to-many relationships.

Relational Model

Table-based model introduced by Edgar F. Codd.

Entity-Relationship (ER) Model

Visualizes entities, attributes, and relationships.

Object-Oriented Model

Combines relational concepts with object-oriented features.

NoSQL Models

Supports unstructured and semi-structured data

Degrees of data abstraction

represent different levels of detail in data modeling, guiding the progression from high-level conceptual models to specific implementation details.

Logical Data Model

• Adds detail to the conceptual model without being specific to any database system

Logical View of Data

Abstract representation of data focusing on entities and relationships.

Normalization

Process of organizing data to reduce redundancy and improve integrity.

First Normal Form (1NF)

Eliminate duplicate columns.

Second Normal Form (2NF)

Ensure all non-key attributes depend on the primary key.

Third Normal Form (3NF)

Remove transitive dependencies

Unique Key

Ensures that all values in a column are unique.

Super Key

A set of attributes that uniquely identifies a record.

Candidate Key

A minimal super key, eligible to be chosen as the primary key

Alternate Key

A candidate key not chosen as the primary key.

Composite Key

A key composed of two or more attributes.

Entity Integrity

Ensures that primary keys are unique and not null.

Referential Integrity

Ensures foreign keys match primary keys in related tables.

Domain Integrity

Enforces valid data types and ranges.

Check Integrity

Defines conditions for valid data entries.

• Entity Integrity

• Referential Integrity

• Domain Integrity

• Check Integrity

DREC

Integrity Rules

• Union

• Union All

• Intersect

• Minus

UUNIM

 Relational Set Operators

Union

Combines result sets, removes duplicates.

Union All

Combines result sets, includes duplicates.

Intersect

Returns common rows between result sets.

Minus

Returns rows in the first result set but not in the second.

Data Dictionary

• Centralized repository of metadata describing the structure of the database.

• Includes table definitions, column definitions, relationships, and constraints.

System Catalog

Maintained by the DBMS, containing metadata about database objects.

• One-to-One

• One-to-Many

• Many-to-Many

Types of relationships

One-to-One

A record in one table is linked to exactly one record in another table.

One-to-Many

 A record in one table is linked to multiple records in another table.

Many-to-Many

Records in one table are linked to multiple records in another table through a junction table.

Data Redundancy

occurs when the same data is stored in multiple places.

index

is a database object that improves the speed of data retrieval.

• Unique Index

• Composite Index

Types of Indexes

Unique Index

Ensures that all values in the indexed column are unique.

Composite Index

 An index on multiple columns.

Codd's rules

are a set of 12 rules proposed by Edgar F. Codd to define what is required from a DBMS to be considered relational.

Cardinality

Specifies the number of instances of one entity associated with another entity

Modality

Describes minimum participation

Entity

Weak Entity

Relationship

Weak Relationship

Attribute

Multivalued Attribute

Zero or one

Many

One

One (and only one)

Zero or many

One or many