SaaS, Big Data, and Communication Protocols

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Questions and Answers

What is a characteristic feature of SaaS applications?

  • They operate without internet connectivity.
  • They are managed by a third-party provider. (correct)
  • They are only available on mobile devices.
  • They require local installation on devices.

Which of the following is NOT a step in the big data analytics process?

  • Munging
  • Data prediction (correct)
  • Visualization
  • Data cleaning

What types of data sources contribute to big data?

  • Printed books and newspapers
  • Weather reports and telephone calls
  • Only sales transaction records
  • Social network videos and sensors (correct)

Why are communication protocols important in IoT systems?

<p>They enable network connectivity. (A)</p> Signup and view all the answers

What term refers to a set of protocols designed to work together?

<p>Protocol stack (B)</p> Signup and view all the answers

Which of the following best describes embedded systems?

<p>A combination of hardware and software designed for specific tasks. (A)</p> Signup and view all the answers

Which of the following is an example of data that can be produced by IoT systems?

<p>Health and fitness data (B)</p> Signup and view all the answers

Which type of device is NOT typically associated with embedded systems?

<p>Desktop computer (B)</p> Signup and view all the answers

What role does data encoding play in communication protocols?

<p>Data representation (B)</p> Signup and view all the answers

Which of the following is a key characteristic of big data?

<p>Diverse in terms of data sources and types. (A)</p> Signup and view all the answers

Flashcards

SaaS (Software as a Service)

Software delivered over the internet, managed by a provider, accessible from any device. Examples: Google Docs, Gmail.

Big Data Analytics

The process of examining large datasets, often structured and unstructured, to extract insights and patterns.

Communication Protocols

Rules that define communication between devices on a network, allowing them to understand and exchange data.

Embedded System

A combination of hardware and software specifically designed for a particular task.

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Data Cleaning

The process of cleaning up data to remove errors, inconsistencies, and redundancies.

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Data Munging

The process of transforming data into a usable format for analysis.

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Data Processing

The process of applying algorithms and computations to analyze data.

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Data Visualization

The process of visualizing data to make it easier to understand and interpret.

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Internet of Things (IoT)

A network of interconnected devices that collect and exchange data with each other.

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Microcontroller

A central processing unit (CPU) that is specifically designed for embedded systems, often with limited resources.

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Study Notes

SaaS Applications

  • SaaS applications are also known as web-based, on-demand, or hosted software.
  • SaaS providers manage security, availability, and performance for these applications.
  • Examples include Google Docs, Gmail, and Office applications.

Big Data Analytics

  • Big data analytics involves studying massive datasets.
  • Big data is characterized by its massive volume, velocity, and variety, making it challenging to manage with traditional databases.
  • Sources of big data include social networks, videos, images, sensors, and sales records.
  • Steps in big data analysis include data cleaning, munging, processing, and visualization.
  • Examples of big data applications include bank transactions, IoT data for vehicle tracking, e-commerce (like Big Basket), and health/fitness data from wearables.

Communications Protocols

  • Communication protocols are essential for IoT systems, enabling network connectivity and application linking.
  • Protocols allow devices to exchange data over networks.
  • Multiple protocols can address different aspects of communication.
  • A group of working protocols is a protocol suite or stack.
  • Applications of protocols include data encoding and addressing schemes.

Embedded Systems

  • Embedded systems are combinations of hardware and software designed for specific tasks.
  • Components include microcontrollers, microprocessors, memory, networking units (e.g., Ethernet, Wi-Fi), input/output units (e.g., displays), and storage (e.g., flash memory).
  • Embedded systems collect data and transmit it to the internet.
  • Examples include digital cameras, DVD players, industrial robots, and wireless routers.

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