Essential IT Concepts: Assets, Networks, Cloud, and Data

Posted on Nov 18, 2024 in Technology

Complementary Assets

Complementary Assets are required to derive value from a primary investment, maximizing its value and success.

Organizational Assets: 1) Supportive culture valuing efficiency; 2) Appropriate business model; 3) Efficient processes; 4) Decentralized authority

Managerial Assets: 1) Strong senior management support; 2) Incentives for innovation; 3) Collaborative environments

Social Assets: 1) Internet and telecommunications; 2) IT education; 3) Standards (government and private)

UPS Case Study

  • Inputs: Package information, signature, pickup/delivery data, location, billing documents.
  • Processing: Data transmission to a central computer for storage and organization by customer, date, driver, etc.
  • Outputs: Pickup/delivery times, location, recipient, reports for accounts, drivers, and management.

Network Types

  • Local Area Network (LAN): Limited geographical area (office, hotspot).
  • Wide Area Network (WAN): Large geographical area (retail chain connecting locations).
  • Internet: Global network connecting millions of devices.
  • Virtual Private Network (VPN): Secure, encrypted connection for remote access.
  • Cloud Computing: Remote servers for data storage and processing (Dropbox, Google Drive).
  • Personal Area Network (PAN): Close proximity devices (Bluetooth).

Client Applications

Thick-Client

  • Pros: Offline capabilities, faster response, advanced features.
  • Cons: Requires updates, maintenance, higher system requirements.

Thin-Client

  • Relies on a central server for processing.
  • Cost-effective, centralized management, accessible from various devices.

Virtualization

PC Virtualization

  • Hosts multiple operating systems on a single PC.
  • Focuses on individual user needs.

Server Virtualization

  • Partitions one server into multiple virtual servers.
  • Optimizes resource use, reduces costs, simplifies management.

Desktop Virtualization

  • Server hosts multiple desktop operating systems for remote access.
  • Enhances security and flexibility.

Load Balancing

  • Distributes tasks across resources for efficiency.
  • Optimizes response time and avoids overloading.
  • Example: Amazon Black Friday (scalability, high availability).

Firmware

Embedded software providing low-level control for hardware devices (e.g., printer code, car electronics).

Internet of Things (IoT)

Interconnected devices communicating via the Internet.

Four Parts Integration:

1. Sensors/Devices (Input): Smart devices send data to the cloud.

2. Data Collection and Connectivity (Input): Data transmission via protocols (HTTP/S, Bluetooth, RFID).

3. Data Processing/Machine Learning (Processing and Output): Automated actions based on data.

4. User Interface (Feedback): User interaction if needed.

Impact: Edge Computing, Industrial IoT, Smart Buildings.

Cloud Types

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Private Cloud

Dedicated to a single organization, offering high security and customization.

Public Cloud

Shared resources provided by third-party vendors.

Fundamental Cloud Services

IaaS (Infrastructure as a Service)

  • Pros: Control over hardware/software, pay-as-you-go, scalable.
  • Cons: Security responsibility, complexity.

PaaS (Platform as a Service)

  • Pros: Cost-effective, easy to use, collaboration.
  • Cons: Limited control, security risks.
  • Example: Google App Engine.

SaaS (Software as a Service)

  • Pros: Scalable, easy to use, no local resources used.
  • Cons: Limited control, compatibility issues, data leaks.
  • Example: HubSpot.

Elasticity & Scalability

Elasticity: Dynamic resource adjustment based on needs.

Scalability: Adding/removing resources without impacting performance.

Pooled Resources

  • Centralized computing resources shared among users.
  • Facilitates load balancing and high availability.

Data Integrity Problem

Data mismatch between rows in a table (e.g., incorrect shipping address).

Lost-Update Problem

Simultaneous updates to the same record by different transactions.

Normalization

Organizing data to reduce redundancy and improve integrity.

Referential Integrity

Ensures consistent relationships between tables (e.g., orders referencing valid customers).

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