Information Systems & Application PDF

Unit One Information System and Their Application Objectives Explain ethical and legal issues in information systems Explain environmental, health, and social issues in information system Recognize the basics of intellectual property rights Describe di...

Unit One Information System and Their Application Objectives Explain ethical and legal issues in information systems Explain environmental, health, and social issues in information system Recognize the basics of intellectual property rights Describe digital identity management Appreciate the role of digital technologies in citizenship 1.1.Impacts of Information System 1.1.1. Ethical and Legal Issues in Information Systems Ethics is concerned with distinguishing right from wrong and plays a vital role in decision-making across various fields, including healthcare, education, and business. ❖ Importance of Ethical Standards: As technology advances, the lack of standardized ethical guidelines in information systems can lead to significant challenges and ethical dilemmas. ❖ Privacy Concerns: The digitization of personal data raises serious privacy issues. Unauthorized access to sensitive information (e.g., emails, social media, banking accounts) poses ethical and legal risks. Organizations must implement measures to protect employee privacy while monitoring computer usage. ❖ Digital Ownership: Digital ownership involves the rights individuals have over their data and content. The ease of copying and sharing online complicates ownership issues. It is unethical to use someone else's digital content without permission, as this undermines the creator's rights and can lead to legal repercussions. ❖ Information Gathering Practices: Many applications collect user data, often without transparent consent processes. This raises ethical questions about the extent and purpose of data collection. Users should critically evaluate requests for personal information to safeguard against data theft and misuse. ❖ Information Security and Liability: Increasing reliance on electronic data exposes organizations to potential security breaches, which can result in identity theft and other 1  malicious activities. Organizations must have protocols in place to handle breaches and report incidents to relevant authorities promptly. ❖ Legal Consequences: Failing to adhere to ethical and legal standards can result in significant legal consequences for individuals and organizations, emphasizing the need for compliance. ❖ Role of Professionals: Various professionals, including those in healthcare and government, must navigate ethical and legal frameworks to maintain public trust and accountability. ❖ Evolving Digital Landscape: The rapid changes in technology necessitate continuous education and awareness regarding ethical and legal issues in information systems. 1.1.2. Social Issues The document discusses the social issues arising from the expansion of information system technologies, highlighting both positive and negative impacts on society. Positive Impacts Access to Technology: Bridges the digital divide, enhancing global connectivity. Advanced Technologies: Use of AI and AR transforms public interactions. Digital Platforms: Widespread use for business and entertainment. Negative Social Issues Socialization Gaps: Increased technology use can reduce family interactions and face-to- face communication among friends. Cyberbullying: Online harassment and the sharing of harmful content can lead to significant emotional distress. Addiction: social media and gaming addictions negatively affect mental health, relationships, and academic performance. Plagiarism: Easy access to information leads to increased instances of academic dishonesty, challenging educational integrity. Cybercrime: The use of computers for illegal activities like fraud and identity theft is on the rise. 2  Job Opportunities and Challenges: Automation and AI create job displacement while also generating new roles, necessitating a shift in required skills. 1.1.3. Environmental Issues Environmental Issues ❖ Impact of Technology: While technology advances, it also poses environmental risks. It consumes resources and power, leading to ecological damage. ❖ E-Waste: Electronic devices contain hazardous materials (e.g., cadmium, lead, mercury) that can contaminate soil and water. Responsible disposal and e-waste management are crucial to minimize harm. 1.1.4. Health Issues ❖ Health Information Systems: Essential for generating quality data in healthcare, improving care delivery, and empowering patients. ❖ Challenges: Unmanaged use of information systems can lead to health problems such as: ✓ Sleep disorders ✓ Stress and loss of productivity ✓ Musculoskeletal issues ✓ Vision problems and obesity 1.2. Intellectual Property Intellectual property rights protect creations of the mind, including software and information systems. Types ✓ Trade Secrets: Confidential information that provides a competitive edge. ✓ Patents: Exclusive rights granted for inventions. ✓ Copyrights: Protect original works of authorship, including software. ✓ Trademarks: Signs that distinguish goods/services. 1.3. Digital Identity Management It is a collection of online information about an individual or organization. Importance: Essential for accessing services like banking and healthcare. 3 Management Practices: Involves limiting data sharing, verifying identity, and correcting personal data. 1.4. Digital Collaboration Definition: Working together using digital tools and technology. Components ❖ People: Central to collaboration, requiring effective communication. ❖ Tools: Various tools enhance collaboration (e.g., communication, documentation, project management). ❖ Devices: Smartphones, tablets, and laptops facilitate digital collaboration. 1.5. Engaging in Citizenship Digital Citizenship: Responsible use of technology to engage positively in society. Key Principles: Use technology to improve communities. Engage respectfully with diverse beliefs. Verify online information sources. 4  Unit Two Emerging Technology Objectives ✓ Describe the meaning and use of Bigdata ✓ Explain cloud computing and fog computing ✓ Apply cloud computing services ✓ Explain the Internet of Things (IoT) and its applications 2.1. Introduction to Bigdata Overview Big Data refers to a collection of data sources that are massive and complex, challenging to process with traditional tools. The explosion of data is driven by the rise of computers, the Internet, and technology that captures information from the physical world. Characteristics of Big Data Big Data is defined by the 5 V's: ❖ Volume: The enormous quantity of data generated from various sources. ❖ Variety: Data exists in multiple formats, including structured (databases), semi-structured (XML, JSON), and unstructured (text, images). ❖ Velocity: The speed at which data is generated and needs to be processed, often in real- time. ❖ Veracity: The trustworthiness and quality of the data, which can vary widely. ❖ Value: The importance of extracting actionable insights from the data, ensuring it serves a purpose. Benefits of Big Data Big Data projects have significant advantages, including: ❖ Customer Acquisition and Retention: Analyzing consumer data improves targeted marketing efforts and enhances customer satisfaction. 5  ❖ Targeted Advertising: Personalized advertising campaigns based on user behavior lead to higher conversion rates. ❖ Product Development: Insights from data can drive innovation and improvements in existing products. ❖ Price Optimization: Data analytics can refine pricing strategies, reducing manual errors and increasing profitability. ❖ Risk Management: Identifying patterns in data helps organizations proactively manage risks. ❖ Improved Decision-Making: Data-driven insights allow for quicker, more informed decisions. Applications of Big Data Big Data is influential across various sectors: ❖ Healthcare: Enhances patient care through predictive analytics and personalized medicine, while also reducing costs. ❖ Education: Utilizes data to tailor educational programs and improve student outcomes. ❖ Banking: Employs analytics for fraud detection, customer segmentation, and regulatory compliance. ❖ Agriculture: Smart farming techniques utilize data for optimal decision-making regarding crop management and resource allocation. ❖ Manufacturing: Predictive maintenance and supply chain optimization improve operational efficiency. ❖ Retail: Data analytics drives personalized shopping experiences and inventory management. ❖ Transportation: Enhances route optimization and traffic management through real-time data analysis. Challenges of Big Data Despite its benefits, Big Data faces several challenges: ❖ Managing Growth: Storing and managing large data sets is complex. The rapid increase in data volume complicates storage and management efforts. 6  ❖ Lack of Professionals: A shortage of skilled data scientists, analysts, and engineers hampers effective Big Data utilization. ❖ Data Security: Safeguarding vast data repositories from cyber threats is a significant concern. ❖ Integration Issues: Combining disparate data sources poses technical challenges and requires robust solutions. 2.2.Cloud Computing 2.2.1. Introduction to Cloud Computing Definition: Cloud computing is the practice of storing and accessing data and computing services over the Internet instead of relying on local servers or personal computers. On-Demand Services: It offers a range of computing services such as servers, data storage, networking, and databases that can be accessed as needed. Accessibility: This model allows multiple users to access data from a single data center, facilitating the storage and retrieval of information without limitations. Real-World Examples: Common cloud-based services include Gmail for email communications, Google Maps for navigation, Amazon for e-commerce, Netflix for entertainment, PayPal for online payments, Spotify for music streaming, and Adobe Creative Cloud for design applications. 2.2.2. Benefits of Cloud Computing Accessibility and Mobility: Users can access tools and data from anywhere, at any time, and on any device with Internet connectivity. This capability supports remote work and enhances collaboration. Data Backup: Cloud service providers back up user data, ensuring it is not lost during service failures, which is crucial for inclusive education through technologies like voice recognition and text-to-speech. Flexibility: Cloud services are highly adaptable, allowing users to easily scale resources up or down based on their needs while only paying for what they use. This flexibility fosters collaboration as users can work together in real-time on shared content. 7  Updating and Scalability: Service providers handle all maintenance and updates, allowing users to concentrate on their work without worrying about software management, thus improving overall efficiency. Optimized Security: Compared to traditional IT infrastructures, cloud computing offers enhanced security measures, addressing challenges businesses face in securing their IT systems due to limited time, expertise, and budget. Controlled Costs: The pay-as-you-go model allows organizations to manage IT costs more effectively, eliminating expenses related to hardware maintenance and upgrades. This model helps reduce overall IT investments and optimizes operational costs. 2.2.3. Limitations of Cloud Computing Server Downtime: No cloud provider can guarantee uninterrupted service, leading to potential access issues during outages, especially if reliant on Internet connectivity. Security and Privacy Issues: Companies often worry about the safety and privacy of sensitive data stored in the cloud, as there is always a risk of breaches despite security measures. Data Ownership and Transparency: Concerns about who owns the data uploaded to cloud services and how it is managed can lead to a lack of trust in cloud providers. Inflexibility: Some cloud providers may impose restrictions on the types of applications and formats that can be used, limiting user flexibility and control over their data. Lack of Support: Compared to traditional hosting services, cloud services may offer minimal customer support, often leaving users to seek solutions through online forums. Cost: While cloud computing can reduce infrastructure costs, hidden fees for additional features can lead to unexpected expenses, necessitating careful management of service agreements. 2.2.4. Types of Cloud Computing A. Public Cloud: A standard model where resources are shared among multiple clients. For example, renting 10GB of public cloud storage means accessing a portion of a larger storage device that is divided among various users. 8  B. Private Cloud: Dedicated resources for a single organization, either managed by a cloud service provider or hosted in the company’s own data center. This model ensures complete control over data security and privacy, making it ideal for sensitive information. C. Community Cloud: A multi-tenant platform used by several organizations within the same industry that share similar security, compliance, and performance concerns. This model provides a collaborative environment while maintaining privacy. D. Hybrid Cloud: Combines elements of both public and private clouds, allowing organizations to host public services in the public cloud while keeping sensitive data in a private cloud environment. This model offers flexibility and comprehensive benefits tailored to organizational needs. 2.2.5 Cloud Computing Services I. Software as a Service (SaaS): A software distribution model where applications are hosted by a vendor and accessed via the Internet. Users subscribe to these services, eliminating the need for local installations and allowing access from any Internet-enabled device. Common SaaS applications include those for accounting, sales, and project management. II. Platform as a Service (PaaS): Provides a cloud-based platform for developers to build, deploy, and manage applications. PaaS includes software support and management services, storage, networking, and tools for collaboration and application maintenance, enabling developers to focus on coding rather than infrastructure. III. Infrastructure as a Service (IaaS): Offers virtualized computing resources over the Internet, providing a complete package for IT infrastructure. IaaS is particularly beneficial for small businesses looking to reduce costs associated with physical hardware, allowing them to scale resources according to their needs. 2.3. Fog Computing Fog computing is an extension of the cloud. Cloud Computing relies heavily on the bandwidth made available, which depends on the capacity of the network service provider. With billions of users processing, sending, and receiving data in and out of the cloud, the system becomes increasingly congested. Fog computing uses the concept of ‘fog nodes’ which are located closer to the data source and have a higher processing and storage capability. Fog provides the missing link 9 for what data needs to be pushed to the cloud, and that can be analyzed locally, at the edge. This makes fog nodes to process data quicker than sending the request to the cloud for centralized processing. What distinguishes fog computing from cloud computing is its closer proximity to small end-users, its wider consumer reach, and better mobility. Rather than requiring devices to go through the network backbone infrastructure, fog computing permits devices to connect directly with their destination with ease and allows them to handle their connections and tasks in any way they see fit. As a result, fog computing improves the quality of service, reduces latency, and enhance user experience. Fog computing smoothly supports the emerging Internet of Things (IoT) physical things (vehicles, home appliances, and even clothes) that are embedded with sensors to enable them to send/receive data. This advantage makes it easier to run a real-time, Big-Data operation with the ability to support billions of nodes in highly dynamic and diverse environments. For example – we can apply fog computing in video surveillance, where continuous streams of videos are large and cumbersome to transfer across networks. 2.4. Internet of Things (IoT) Definition: The Internet of Things (IoT) refers to a network of physical objects or "things" equipped with software, electronics, networks, and sensors to collect and exchange data. It aims to extend Internet connectivity beyond traditional devices like computers and smartphones to everyday objects. Functionality: IoT enables remote control of devices across a network, reducing human effort and facilitating easy access to connected devices. It employs Artificial Intelligence algorithms and data collection to enhance user experiences, transforming ordinary items into smart systems. Examples of IoT Devices: IoT can include various devices such as animal tracking devices, diabetes monitors, air conditioning sensors that adjust temperature automatically, and smart wearables. 10  Application: When an object connects to the Internet, it gains the ability to send and receive data, creating opportunities by linking computer systems with the physical world. 2.4.1. Major Advantages of IoT ❖ Efficiency: IoT enables the collection of real-time data, translating it into useful information for businesses, thus improving resource consumption and productivity. ❖ Technical Optimization: Users can control multiple devices from a single platform, simplifying tasks such as adjusting TV volume or thermostat settings. ❖ Convenience: IoT enhances customer experience by providing quick and high-quality solutions tailored to user needs. ❖ Improved Customer Experience: Businesses can better understand customer pain points and offer personalized solutions, leading to enhanced satisfaction. ❖ Conservation: IoT contributes to environmental conservation by monitoring resources like traffic, water, and electricity usage, aiding in the development of smart cities. ❖ Personalization: IoT devices learn user preferences, enabling more tailored services based on individual choices. 2.4.2. Limitations of IoT ❖ Security and Privacy: The widespread use of IoT raises concerns about data security, especially in sensitive sectors like healthcare and banking. Compliance with global information privacy regulations is becoming increasingly important. ❖ Connectivity and Power Dependence: Many IoT devices require constant Internet access and power; outages can disrupt functionality. ❖ Complexity and Integration: IoT technology can be complex, with challenges in maintenance and deployment. Compatibility issues may arise due to varying protocols and standards among manufacturers. ❖ Higher Cost: Deploying IoT devices often involves significant financial investment for purchasing, setting up, and installing devices, leading to increased overall costs. 2.4.3. How Does IoT Work? An IoT system consists of four key components: ❖ Sensors/Devices: These collect data from the environment. Various sensors (e.g., temperature, humidity, motion) can be integrated into devices like smartphones. 11 ❖ Connectivity: Data is transmitted to the cloud via methods such as cellular, satellite, Wi- Fi, Bluetooth, or Ethernet, depending on the application. ❖ Data Processing: The collected data is processed in the cloud, which can involve simple checks (like temperature limits) or complex analyses (like video monitoring). ❖ User Interface: Information is relayed to the end-user through alerts (email, text, notifications). Users can also interact with the system, such as adjusting settings remotely or allowing the system to take automated actions based on predefined rules. 12  Unit 3 Database Management System (DBMS) Objectives At the end of this unit, students will be able to: Describe relational database management system. Explain fields and records. Apply SQL data definition language (DDL) to create tables in a database. Differentiate between SQL data definition language (DDL), data manipulation language (DML), and data query language (DQL). Apply SQL DML to manipulate records in tables. Apply SQL DQL to query records of tables. 3.1. Overview of Relational Database Management Systems A Relational Database Management System (RDBMS) is a type of software that facilitates the creation, maintenance, and controlled access to databases. It is based on the relational data model, which organizes data into structured tables. Structure of Data: Tables: The core structure of an RDBMS, consisting of rows and columns. ❖ Rows (Records/Tuples): Each row corresponds to a single data entry, representing an instance of an entity (e.g., a student). ❖ Columns (Attributes/Fields): Each column represents a property of the entity (e.g., student ID, name, age, grade level, sex). Note: Attributes: Attributes define the characteristics of an entity. For instance, a student entity can be described with attributes like: o Student ID (integer) o Name (text) o Age (integer) o Grade Level (text) o Sex (text) 13 Data Types: Each attribute must be assigned a specific data type, which dictates the kind of data that can be stored. Common data types include: Text: For strings of characters. Integer: For whole numbers. Real Numbers: For decimal values. Date: For date values. Currency: For monetary values. Boolean: For true/false values. Examples of Popular RDBMS: Microsoft Access: A user-friendly database management tool integrated with Microsoft Office. Oracle: A comprehensive and powerful RDBMS widely used in enterprise applications. Microsoft SQL Server: A robust database solution for business applications. MySQL: An open-source RDBMS known for its reliability and performance. SQLite: A lightweight, embedded database solution. IBM DB2: A scalable database management system designed for large-scale applications. PostgreSQL: An advanced open-source RDBMS with strong support for complex queries. 3.2. Database Manipulation Using SQL SQL (Structured Query Language) is the standard language used for managing and manipulating relational databases. It allows users to perform various operations on the data stored in RDBMS. Microsoft Access is the default relational database program installed with the Microsoft Office package. It offers the functionality of a database, and the programming capabilities to create databases easily and navigate records. SQL command in Microsoft Access can be used to implement and manipulate. 3.2.1. Data Definition Language (DDL): This category includes commands that define the database structure. It includes sql commands like CREATE, DROP, and ALTER. A. CREATE command: Used to create a new table in the database. Syntax: CREATE TABLE table_name (Column1 datatype [Primary Key], [Column2 datatype] [REFERENCES table_name2(Column1)],...); 14  Primary Key: A unique identifier for each record in the table. Foreign Key: A field that links to the primary key of another table, establishing relationships. B. ALTER TABLE: Modifies an existing table's structure. Adding column: ALTER TABLE Table_Name ADD Column_Name data_type; Dropping column: ALTER TABLE Table_Name DROP Column_Name; Modifying a column: ALTER TABLE table_name MODIFY Column_Name new_datatype; Adding foreign key: ALTER TABLE child_table ADD CONSTRAINT fk_parent FOREIGN KEY (parent_id) REFERENCES parent_table(parent_id); C. DROP TABLE: Deletes a table and all its data from the database. Syntax: DROP TABLE table_name; 3.2.2. Data Manipulation Language (DML): This category focuses on manipulating the data within the tables. It includes INSERT, UPDATE, and DELETE sql commands. I. INSERT Command: Adds new records to a table. ❖ Option 1: INSERT INTO table_name VALUES (value1, value2, value3...); ❖ Option 2: INSERT INTO table_name (column1, column2…) VALUES (value1, value2 …); II. UPDATE Command: Modifies existing records in a table. Syntax: UPDATE table_name SET column1 = value1, column2 = value2... WHERE condition; III. DELETE Command: Removes records from a table Syntax: DELETE FROM table_name WHERE condition; To delete all records: DELETE FROM table_name; 3.2.3. Data Query Language (DQL): Primarily involves querying data using the SELECT command. SELECT Command: Retrieves data from one or more tables. Syntax: SELECT * FROM table_name; Selecting Specific Columns: Allows users to specify which columns to retrieve. Syntax: SELECT field1, field2 FROM table [WHERE criterion]; 15  Filtering Records: The WHERE clause is used to filter results based on specific conditions. ORDER BY Clause: Sorts the results based on specified columns. Syntax: SELECT column1, column2 FROM table_name ORDER BY [column] [ASC|DESC]; Joining Tables: The SELECT command can also be used to retrieve data from multiple related tables, enhancing the richness of the query results. Selecting records from Two Tables: Syntax: SELECT table1.column1, [table1.column2], table2.column1, [table2.column2] FROM table1, table2 WHERE table1.column1 = table2.column2; 16