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COMPUTING AND DATA PROCESSING - Coggle Diagram
COMPUTING AND DATA PROCESSING
Introduction to Information Systems
Information systems are organized combinations of people, technology, data, and procedures that collect, process, store, and distribute information to support an organization's activities and decision-making.
Concept and evolution: Information systems have evolved from manual processes to digital platforms that use automation, cloud computing, and artificial intelligence.
Types of information systems:
Transaction Processing Systems: Record routine operations, such as sales and payments.
Management Information Systems: Generate reports to support administrative activities.
Decision Support Systems: Help analyze information and evaluate alternatives.
Strategic Information Systems: Support long-term planning and competitive advantage.
Knowledge-Based Systems: Use stored knowledge and specialized rules to support problem-solving.
Components of information systems: Include hardware, software, databases, telecommunications networks, people, and procedures.
Role in organizations: Improve productivity, facilitate communication, reduce errors, and support decision-making.
Advantages and limitations: They provide speed, accuracy, and access to information, but may involve implementation costs, technical problems, and security risks.
Digital environment: Includes cloud computing, big data, artificial intelligence, and other technologies that improve information management.
Information Management and Analysis
Information management and analysis involve collecting, organizing, storing, interpreting, and distributing data to generate useful knowledge and support informed decisions.
Data collection and storage: Gathering information from different sources and storing it in an organized way.
Information sources:
Primary sources: Data collected directly through surveys, interviews, observations, or experiments.
Secondary sources: Existing information obtained from reports, databases, publications, and previous studies.
Data preparation: Cleaning, classifying, organizing, and checking data to improve its quality and reliability.
Data analysis: Examining data to identify patterns, relationships, trends, and possible conclusions.
Descriptive analysis: Summarizes what the data shows.
Inferential analysis: Uses sample data to draw conclusions about a larger population.
Data mining: Identifies patterns and relationships in large datasets.
Machine learning: Uses algorithms that learn patterns from data to make predictions or classifications.
Data visualization: Presents findings through charts, graphs, and dashboards to facilitate interpretation.
Information distribution: Shares relevant information with the appropriate users through suitable communication channels.
Ethics and responsibility: Require accurate information, transparency, privacy protection, and responsible data use.
Data Processing Tools
Data processing tools are computer programs and technological applications used to collect, organize, calculate, analyze, present, and share information.
NoSQL databases: Manage flexible or non-tabular data structures.
Distributed databases: Store data across multiple interconnected systems.
Relational databases: Organize data into related tables.
Cloud databases: Allow data storage and access through online services.
Databases: Systems used to store, organize, retrieve, and manage large amounts of data.
Word processing software: Used to create, edit, format, and share documents.
Integrative Project in Computing and Data Processing
An integrative project combines the knowledge and skills developed throughout the course to identify a real problem and propose a practical solution using computing tools and effective data management.
Problem identification: Defines the situation, need, or organizational challenge that the project intends to address.
Project objectives: Establishes the expected results and the goals to be achieved.
Data processing strategy: Determines how information will be collected, organized, processed, analyzed, and stored.
Selection of technological tools: Chooses suitable software, databases, and digital platforms according to the project's needs.
Information Flow and Representation
Information flow and representation refer to the processes through which data is collected, organized, transformed into meaningful information, represented visually or textually, and communicated to the people who need it.
Information representation: Presents information through tables, charts, graphs, diagrams, and reports to make it easier to interpret.
Information communication and flow: Ensures that information reaches the appropriate people at the right time and in a useful format.
Data processing: Transforms raw data into useful information through calculations, classification, sorting, and analysis.
Importance in organizations: Improves coordination, supports decision-making, and helps identify problems and opportunities.
Information organization: Structures data logically so it can be understood and retrieved easily.
Computer Security and Data Protection
Computer security and data protection involve the measures, policies, and technologies used to safeguard computer systems and information against unauthorized access, alteration, loss, theft, or destruction.
Cybersecurity: Protects computers, networks, applications, and information from digital threats.
Fundamental security principles:
Confidentiality: Ensures that only authorized people can access information.
Integrity: Ensures that information remains accurate and has not been improperly altered.
Availability: Ensures that information and systems are accessible when needed.
Security threats: Include viruses, malware, phishing, unauthorized access, data theft, and system failures.
Access control: Regulates who can use systems and information.
Identification: Establishes a user's claimed identity.
Authentication: Verifies that identity.
Authorization: Determines which resources the user is allowed to access.
Backup and recovery: Protect data by creating copies that can be restored after loss or damage.
Full backup: Copies all selected data.
Incremental backup: Copies changes made since the most recent backup.
Differential backup: Copies changes made since the last full backup.
Cryptography: Protects information by transforming it into a form that unauthorized people cannot easily understand.
Symmetric encryption: Uses the same key to encrypt and decrypt data.
Asymmetric encryption: Uses a public key and a private key.
Personal data protection: Involves respecting privacy, handling personal information responsibly, and complying with applicable laws and regulations.