IT Fundamentals Quiz

Data Analytics

• Definition: The process of extracting insights and patterns from data to inform business decisions.
• Key concepts:
  • Data mining: discovering patterns and relationships in large datasets.
  • Data visualization: presenting data in a graphical format to facilitate understanding.
  • Predictive analytics: using statistical models to forecast future outcomes.
• Tools and techniques:
  • Data warehousing: storing data in a central repository for analysis.
  • Business intelligence: using data to inform business decisions.
  • Machine learning: using algorithms to identify patterns and make predictions.

Database Management

• Definition: The process of designing, implementing, and maintaining databases to store and manage data.
• Key concepts:
  • Data modeling: designing the structure of a database.
  • Data normalization: organizing data to minimize redundancy and improve data integrity.
  • Database performance tuning: optimizing database performance for efficient data retrieval.
• Database types:
  • Relational databases (RDBMS): storing data in tables with defined relationships.
  • NoSQL databases: storing data in a variety of formats for flexible schema design.

Network Security

• Definition: The practice of protecting computer networks from unauthorized access, use, disclosure, disruption, modification, or destruction.
• Key concepts:
  • Firewalls: controlling incoming and outgoing network traffic based on security rules.
  • Encryption: protecting data in transit using secure protocols (e.g., SSL/TLS).
  • Access control: restricting user access to network resources based on identity and permissions.
• Threats and vulnerabilities:
  • Malware: malicious software designed to harm or exploit computer systems.
  • Phishing: social engineering attacks to trick users into revealing sensitive information.

Artificial Intelligence

• Definition: The development of computer systems that can perform tasks that typically require human intelligence.
• Key concepts:
  • Machine learning: training algorithms to learn from data and make predictions or decisions.
  • Natural language processing (NLP): enabling computers to understand and generate human language.
  • Computer vision: enabling computers to interpret and understand visual data from images and videos.
• AI applications:
  • Chatbots: conversational interfaces for customer service or support.
  • Recommendation systems: suggesting products or services based on user behavior and preferences.

Cloud Computing

• Definition: The delivery of computing resources and services over the internet on-demand and pay-per-use basis.
• Key concepts:
  • Infrastructure as a Service (IaaS): providing virtualized computing resources over the internet.
  • Platform as a Service (PaaS): providing a complete platform for developing and deploying applications.
  • Software as a Service (SaaS): providing software applications over the internet.
• Cloud deployment models:
  • Public cloud: sharing resources with other customers in a multi-tenant environment.
  • Private cloud: dedicated resources for a single organization.
  • Hybrid cloud: combining public and private cloud resources for flexibility and scalability.