2. DATABASE MODELING_Database Fundamentals.pptx

Prepared by: Eng. Javier Daza Piragauta

DATABASE
FUNDAMENTALS
Teacher: Eng. Javier Daza
April 8, 2024

Content
 Welcome greeting
 Pedagogical agreements: mutual recognition,
present course overviews, and make possible
academic commitments, among other
agreements.
 Database Modeling Syllabus
 The current context of Database
 History and evolution of Database
April 8, 2024

Content
4. Context of Relational Databases
 Gartner Technology Trends and CES 2024.
 Introduction to Relational Databases
April 8, 2024

QUESTION FOR CLASS
What are the Gartner Top 10 Strategic
Technology Trends for 2024?
April 8, 2024

What are the Gartner Top 10 Strategic Technology Trends for 2024?
1. AI Trust, Risk and Security Management (AI TRiSM)
2. Continuous Threat Exposure Management (CTEM)
3. Sustainable Technology
4. Platform Engineering
5. AI-Augmented Development
6. Industry Cloud Platforms
7. Intelligent Applications
8. Democratized Generative AI
9. Augmented Connected Workforce
10.Machine Customers
Gartner Top 10 Strategic Technology Trends for 2024
April 8, 2024
1. Context of Database

QUESTION FOR CLASS
What are the most outstanding technologies of
CES 2024?
April 8, 2024

What are the most outstanding technologies of CES 2024?
1. Televisions
2. Smart Devices
3. Robots focused on transportation and mobility
4. Virtual Reality Headset for Health Monitoring
5. Artificial Intelligence – Metaverse
6. Sustainable Technology
7. Semiconductor self-sufficiency
8. Internet of Thing – IoT
9. Flying electric cars and boats
Great technological innovations at the CES 2024
April 8, 2024

Content
UNIT 1.Context of relational databases
 History and evolution of databases
 General definition of Databases
 Types of databases
 Characteristics and objectives of the databases
 Advantages
 Relational and non-relational databases
 Profiles within a Database
 Database Structures (Hierarchical, Network, Relational)
April 8, 2024

CLASS ACTIVITY
Database History
Video
April 8, 2024

CLASS ACTIVITY
PRETEST
QUIZ -
April 8, 2024

History and evolution of databases
The history of databases is a fascinating journey, spanning
centuries and evolving alongside technological advancements.
Below is a brief summary of its evolution:
 Early Days (Pre-computers):
 Record-keeping: Information was stored on physical media like
clay tablets, papyrus scrolls, and later, paper files and ledgers.
 Manual retrieval: Finding specific information was a laborious
process, requiring manual searching and sorting.
April 8, 2024

 1950s-1960s: Emergence of Electronic Databases:
 First database systems: Developed for managing large datasets
in government and business, using punch cards and early
computers.
 Hierarchical and Network models: Data was organized in tree-
like or network structures, limiting flexibility and efficiency.
April 8, 2024

 1970s: The Relational Revolution:
 Edgar F. Codd's Relational Model: A groundbreaking paper laid
the foundation for modern relational databases. Data stored in
tables with relationships between them, allowing for flexible
and efficient querying.
 SQL (Structured Query Language): Standardized language for
interacting with relational databases, simplifying data
manipulation and retrieval..
April 8, 2024

 1980s-1990s: Widespread Adoption and Growth:
 Relational databases become dominant: Companies like Oracle,
Microsoft, and IBM develop popular relational database
management systems (RDBMS).
 Increased focus on performance and scalability: Advances in
hardware and software enable handling larger datasets
efficiently.
April 8, 2024

 2000s-Present: Diversification and New Challenges:
 NoSQL databases emerge: Offering alternative data models
(e.g., document, key-value) for handling large, unstructured
data and high-performance applications.
 Cloud computing and Big Data: Databases move to the cloud,
facilitating data storage, access, and analytics on a massive
scale.
 Focus on security, privacy, and integration: Addressing rising
concerns about data security and protecting user privacy, while
seamlessly integrating with various applications and services.
April 8, 2024

 Key reflections
 The history of databases reflects a continuous effort to manage
information more efficiently and effectively.
 From manual record-keeping to sophisticated cloud-based
systems, the evolution has been driven by advances in
technology and changing data needs.
 Today, we see a diverse landscape of databases with different
strengths and use cases, requiring careful selection based on
specific requirements.
April 8, 2024

 Key reflections
 The future of databases likely involves further breakthroughs in
artificial intelligence, machine learning, and distributed
computing, shaping how we store, access, and analyze data.
 Understanding the history and evolution of databases helps us
appreciate the current landscape and make informed decisions
about data management strategies.
April 8, 2024

General definition of Databases
1. What are relational databases?
They are digital systems that store data in tables, similar to
spreadsheets.
These tables consist of rows and columns, where each row
represents a unique record, and each column represents a specific
attribute of that record.
The key feature is the relationship between tables. Imagine
linking books in a library by author, genre, or publication date.
Similarly, databases connect tables through shared fields, allowing
you to retrieve and analyze data across them.
April 8, 2024

2. Formal Definition:
A database is a self-contained, integrated collection of
structured data, logically organized and designed to efficiently
manage and access the data by authorized users.
Reference: Codd, E.F. (1970). A Relational Model of Data for
Large Shared Data Banks. Communications of the ACM, 13(6),
377-387. (https://dl.acm.org/doi/10.1145/362384.362685)
April 8, 2024

3. Functional Definition:
A database is a software system that allows you to create, store,
organize, and retrieve information electronically. It acts as a
centralized repository for data, enabling efficient manipulation,
analysis, and sharing.
Reference: Elmasri, R., & Navathe, S.B. (2017). Fundamentals
of Database Systems (7th ed.). Pearson Education.
April 8, 2024

4. User-Centric Definition:
A database is a digital filing cabinet that stores and organizes
information in a structured way, making it easy to find and use
what you need. It helps you manage various data types efficiently,
whether it's customer information, product details, or financial
records.
Reference: Date, C.J. (2012). Introduction to Database Systems
(13th ed.). Addison-Wesley Longman.
April 8, 2024

Why are they important?
 Structured organization: Data is neatly organized and easily
searchable, unlike text documents or spreadsheets.
 Efficient access: Quickly find specific information through
queries, like searching for books by author in a library catalog.
 Data integrity: Relationships between tables maintain data
consistency and prevent duplication.
 Scalability: Databases can store massive amounts of data and
grow as your needs evolve.
April 8, 2024

Types of databases
The diverse world of databases offers various solutions depending on your specific
data needs and requirements. Below are the 5 most representative types of databases
1. Relational Databases:
 Structure: Data is organized in tables with rows and columns, connected by
relationships (e.g., foreign keys).
 Strengths: Structured data, robust querying capabilities, ACID compliance
(ensuring data integrity).
 Weaknesses: Less efficient for unstructured data, scalability limitations for massive
datasets.
 Popular examples: MySQL, Oracle, Microsoft SQL Server, PostgreSQL, MySQL.
Reference: Elmasri, R., & Navathe, S.B. (2017). Fundamentals
of Database Systems (7th ed.). Pearson Education.
April 8, 2024

Types of databases
2. NoSQL Databases:
 Structure: Offer flexible data models like document, key-value, and graph, suitable
for unstructured and semi-structured data.
 Strengths: Highly scalable, handle large datasets efficiently, ideal for diverse data
types.
 Weaknesses: May lack strict data consistency compared to relational databases,
require specific query languages.
 Popular examples: MongoDB, Cassandra, Redis, Neo4j.
Reference: Fowler, M. (2010). NoSQL: NoSQL databases for
modern web apps. Manning Publications.
April 8, 2024

Types of databases
3. Object-Oriented Databases:
 Structure: Store data as objects, encapsulating data and associated methods,
similar to object-oriented programming languages.
 Strengths: Closely integrated with object-oriented applications, provide natural
data representation for complex objects.
 Weaknesses: Less widely used compared to other types, may require specialized
expertise.
 Popular examples: Gemstone, ObjectDB, Versant.
Reference: Cattell, R.G.G., & Barry, D.K. (2000). The Object
Database Standard: ODMG 3.0. Morgan Kaufmann
Publishers.
April 8, 2024

Types of databases
4. Cloud Databases:
 Delivery model: Databases hosted and managed by cloud providers like Amazon
Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
 Strengths: Easy scalability, pay-as-you-go pricing, automatic maintenance and
updates.
 Weaknesses: Potential vendor lock-in, security concerns in some cases.
 Popular examples: Amazon RDS, Azure Cosmos DB, Google Cloud SQL.
Reference: Stonebraker, M., Hamilton, J., & Kereš, S. (2017).
Database-as-a-Service: From Concepts to Hands-on Practice.
Morgan Kaufmann Publishers
April 8, 2024

Types of databases
5. Graph Databases:
 Structure: Represent data as nodes (entities) and relationships (connections)
between them, ideal for modeling complex interconnected data.
 Strengths: Efficiently navigate and query relationships, valuable for social
networks, recommendation systems, and fraud detection.
 Weaknesses: Can be more complex to manage compared to relational databases,
limited query languages in some cases.
 Popular examples: Neo4j, Amazon Neptune, OrientDB.
Reference: Robinson, I., Webber, J., & Erosa, E. (2015). Graph
Databases: New Opportunities for Connected Data. O'Reilly
Media.
April 8, 2024

April 8, 2024
Content
UNIT 1.Context of relational databases
 History and evolution of databases
 General definition of Databases
 Types of databases
 Characteristics and objectives of the databases
 Advantages
 Relational and non-relational databases
 Profiles within a Database
 Database Structures (Hierarchical, Network, Relational)
April 8, 2024

Characteristics and Objectives of Relational
Databases
Relational databases have dominated the data management landscape for decades
due to their structured approach and versatility. Here's a breakdown of their key
characteristics and objectives:
Characteristics:
 Structured Data: Information is organized in tables with rows (records) and columns
(attributes), defining data types and relationships.
 Relationships: Tables are linked through defined relationships (e.g., foreign keys),
enabling efficient retrieval of related data.
 Data Independence: Changes to the structure of one table generally don't impact
others, promoting flexibility and maintainability.
 Standardized Language: SQL (Structured Query Language) provides a universal
language for interacting with relational databases.
 ACID Compliance: Transactions adhere to Atomicity, Consistency, Isolation, and
Durability principles, ensuring data integrity.
April 8, 2024

Databases
Objectives:
 Data Integrity: Maintains accurate and consistent data by enforcing data types,
constraints, and relationships.
 Efficient Data Retrieval: Allows for fast and flexible querying of data based on
specific criteria using SQL.
 Data Sharing and Collaboration: Enables controlled access and manipulation of data
by authorized users, facilitating collaboration.
 Data Security: Provides mechanisms for user authentication, authorization, and
data encryption to protect sensitive information.
 Data Standardization: Encourages a consistent data model within an organization,
simplifying data integration and analysis.
April 8, 2024

Databases
Strengths:
 Ideal for structured data with well-defined relationships.
 Powerful querying capabilities for complex data retrieval.
 ACID (Atomicity, consistency, isolation and durability)compliance ensures data
integrity and reliability.
 Standardized language (SQL) makes it widely accessible and adaptable.
 Well-established technology with mature tools and expertise available.
 Weaknesses:
 Less efficient for large volumes of unstructured data.
 Scalability limitations for massive datasets can be an issue.
 Complex schema design and data modeling can be time-consuming.
 Requires familiarity with SQL for advanced data manipulation.
April 8, 2024

Advantages of relational databases over file
systems
The advantages of relational databases over file systems, addressing any potential
issues from previous responses:
Data Integrity and Consistency:
 Structure and Constraints: Relational databases enforce data types, constraints
(e.g., primary keys, unique values), and relationships, ensuring data accuracy and
consistency. This reduces errors and discrepancies compared to file systems, where
data can be duplicated, inconsistent, or lack validation.
 Normalized Data: By minimizing redundancy through data normalization, relational
databases avoid issues like inconsistent information across multiple files and
simplify updates.
April 8, 2024

systems
Data Access and Manipulation:
 Powerful Querying: SQL provides a standardized and versatile language for
retrieving specific data from relational databases based on complex criteria. This
contrasts with the limited search and filtering options offered by file
systems, requiring manual and less efficient data manipulation.
 Relationships and Joins: Relational databases excel at joining data across
multiple tables based on defined relationships, allowing for comprehensive
analysis and insights into data connections. Joining data in file systems is often
manual and tedious.
April 8, 2024

systems
Data Management and Security:
 Centralized Control: Relational databases offer a central repository for data,
simplifying management, backups, and access control. File systems often scatter
data across various locations, making administration and security complex.
 Granular Access Control: Relational databases allow fine-grained user access
control, assigning different permissions based on user roles. File systems typically
rely on basic folder permissions, limiting security and data privacy..
April 8, 2024

systems
Additional Advantages:
 Data Integrity Validation: Many relational databases have built-in validation
mechanisms to catch errors during data entry, further enhancing accuracy.
 Transaction Management: ACID (Atomicity, Consistency, Isolation, Durability)
principles guarantee data integrity during transactions in relational databases,
ensuring reliable data updates.
 Data Sharing and Collaboration: Relational databases facilitate collaboration by
providing controlled access and manipulation of data for authorized users.
April 8, 2024

systems
Addressing Potential Issues:
 Simplicity: While file systems may seem simpler on the surface, managing
relational databases is well-supported with mature tools and expertise available.
 Scalability: Scalability concerns for relational databases with massive datasets
can be mitigated through optimized design and database clustering solutions.
 Schema Design: While schema design can be complex, it lays the foundation for
efficient data management and can be iteratively refined over time.
April 8, 2024

Relational and non-relational databases
Relational databases
 Structure: Data is organized in tables with rows and columns, like a spreadsheet.
Each table represents a specific entity, and the columns represent the attributes
of that entity.
 Relationships: Tables can be linked together using relationships, which are
defined by foreign keys. This allows you to query data from multiple tables at the
same time.
 Queries: You can use SQL (Structured Query Language) to query data from a
relational database. SQL is a powerful language that allows you to select, insert,
update, and delete data.
 Examples: MySQL, Oracle Database, Microsoft SQL Server, PostgreSQL
April 8, 2024

Non-relational databases
 Structure: Data can be stored in a variety of formats, such as documents, key-
value pairs, or graphs. There is no fixed schema, so data can be more flexible.
 Relationships: Relationships between data items are not as strictly defined as in
relational databases. They may be stored within the data itself or defined using
separate mechanisms.
 Queries: Non-relational databases often use their own query languages, which
are less standardized than SQL.
 Examples: MongoDB, Cassandra, Redis, Neo4j
April 8, 2024

Which type of database is right for you?
The best type of database for you will depend on your specific needs. Here are
some factors to consider:
 The type of data you are storing: If you are storing structured data with well-
defined relationships, a relational database may be a good choice. If you are
storing unstructured data or data with flexible relationships, a non-relational
database may be a better option.
 The size of your data: Relational databases can be efficient for small to medium-
sized datasets. However, they can become less efficient as the size of the data
grows. Non-relational databases can be more scalable and can handle larger
datasets more efficiently.
April 8, 2024

Which type of database is right for you?
 Your performance needs: If you need to perform complex queries on your data,
a relational database may be a better choice. However, if you need to quickly
insert or update data, a non-relational database may be a better option.
 Your budget: Relational databases can be more expensive to license and
maintain than non-relational databases.
April 8, 2024

Profiles within a Database
1. User Profiles:
Definition: Individual records within a database storing information about
users of a system or application.
Examples: Name, email address, login credentials, preferences, settings,
history of activity.
Benefits: Personalized experiences, targeted marketing, improved security,
access control.
Considerations: Privacy concerns, data security, managing user consent..
April 8, 2024

2. Customer Profiles:
Definition: Records containing information about customers or clients of a
business.
Examples: Demographics, purchase history, preferences, interests, contact
information.
Benefits: Targeted marketing, customer segmentation, product
recommendations, personalized offers.
Considerations: Customer privacy, data management regulations, ethical use
of data..
April 8, 2024

3. Entity Profiles:
Definition: Records in a database describing specific entities of interest, like
products, assets, or resources.
Examples: Product specifications, financial information, maintenance
history, location data.
Benefits: Improved asset management, data-driven decision making,
efficiency gains.
Considerations: Data integration across systems, data quality, maintaining
accurate profiles..
April 8, 2024

4. Role-Based Profiles:
Definition: Profiles defining permissions and access levels for different user
roles within a system.
Examples: Admin, editor, viewer, moderator, guest, etc.
Benefits: Improved security, granular access control, role-based permissions.
Considerations: Defining clear roles, managing user assignments, preventing
unauthorized access..
April 8, 2024

5. Metadata Profiles:
Definition: Information about the structure and characteristics of data
within a database.
Examples: Data types, constraints, relationships, descriptions, ownership.
Benefits: Improved data understanding, data governance, data quality
control.
Considerations: Maintaining accurate metadata, version control, accessibility
for authorized users..
April 8, 2024

Database Structures (Hierarchical, Network,
Relational)
Database structures play a crucial role in organizing and managing data
efficiently. Here's a breakdown of three key types:
1. Hierarchical Database:
Structure: Imagine an upside-down tree, with the root node at the top,
representing the most general category. Child nodes branch out below,
representing increasingly specific subcategories, forming a parent-child
relationship.
Strengths: Simple to understand and implement, efficient for data with clear
hierarchical relationships (e.g., organization structure, file systems).
Weaknesses: Limited flexibility for complex relationships, difficult to represent
many-to-many relationships, limited querying capabilities.
Examples: File systems, early inventory management systems..
April 8, 2024

Relational)
2. Network Database:
Structure: More flexible than hierarchical, allowing more than one parent
node for individual records. Think of it as a web of interconnected nodes, where
each node represents data and edges represent relationships.
Strengths: Handles complex relationships better than hierarchical, offers more
data flexibility, good for modeling interconnected data (e.g., social networks,
transportation systems).
Weaknesses: Can be more complex to design and manage, querying can be
challenging, not as widely used as other models.
Examples: Social media platforms, geographical information systems (GIS)..
April 8, 2024

Relational)
3. Relational Database:
Structure: Data is organized in tables with rows (records) and columns
(attributes). Relationships between tables are established through foreign
keys, allowing complex data connections.
Strengths: Highly structured, powerful querying capabilities (SQL), ACID
compliance (ensuring data integrity), widely used and supported.
Weaknesses: Less flexible for unstructured data, scalability limitations for
massive datasets.
Examples: MySQL, Oracle Database, Microsoft SQL Server, PostgreSQL..
April 8, 2024

Academic activity
in class by teams
QUIZZ
April 8, 2024

Academic activity
in class by teams
April 8, 2024

Sources
• Adoración, De miguel. Diseño de bases de Datos relacionales. Madrid. Editorial RAMA. 1999.
• Adoración, De miguel. Mario G Piattini Velthuis. Fundamentos y modelos de bases de datos.
Alfaomega Grupo Editor Rama Editorial, 1999
• Adoración, De miguel. Mario G Piattini Velthuis. Diseño de bases de datos: problemas
resueltos. Alfaomega - Ra-ma.
• Johnson, James L. Bases de datos modelos, lenguajes, diseño. Oxford University Press 2000
• Rob, Peter. Sistemas de bases de datos diseño, implementación y administración. Thomson
Editores. 2004.
• Fundamentos de sistemas de bases de datos de Silberschatz
• CARCAMO SEPÚLVEDA JOSÉ; Bases de Datos Relacionales. J. Ediciones UIS
• KENNETH LAUDON; Administración de los Sistemas de Información. Prentice Hall.
• TIZNADO. MARCO; El camino fácil a Access. Ed. Mc Graw Hill
• PIÑEIRO GOMEZ JOSE MANUEL; Definición y manipulación de datos. Ediciones Paraninfo, S.A.
April 8, 2024

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Thank you!
Comments & Questions
April 8, 2024

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