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IoT Processing Topologies and Types

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Questions and Answers

What are the two types of data mentioned in the text?

Big and small

Text and image

SQL and RDBMS

Unstructured and structured (correct)

What are examples of structured data mentioned in the text?

Videos and audio files

Phone numbers and social security numbers (correct)

PDFs and Word docs

Sensor nodes and automated monitoring systems

What is used for accessing structured data in RDBMS?

PDFs

Structured Query Language (SQL) (correct)

E-mails

Videos

Which category of data has a pre-defined structure?

Structured data Signup and view all the answers

What characterizes unstructured data?

Variability and lack of pre-defined structure Signup and view all the answers

What contributes to the massive volume of data on the Internet, in addition to user-generated data?

Automated monitoring systems Signup and view all the answers

Study Notes

Types of Data

Data is primarily categorized into structured and unstructured types.

Examples of Structured Data

Examples include data organized in tables with rows and columns, such as databases, spreadsheets, and data warehouses.

Accessing Structured Data in RDBMS

Structured Query Language (SQL) is utilized for accessing and managing structured data in Relational Database Management Systems (RDBMS).

Pre-defined Structure of Data

Structured data is characterized by its pre-defined schema, which dictates how the data is organized, stored, and accessed.

Characteristics of Unstructured Data

Unstructured data lacks a specific format or organization, making it difficult to categorize or analyze. It includes text documents, images, videos, and social media posts.

Contributors to Internet Data Volume

Aside from user-generated content, the massive volume of data on the Internet is also driven by machine-generated data, such as sensor data, logs, and transactional records.

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Description

Explore the various processing topologies and types relevant to the Internet of Things (IoT) and the vast quantities of data generated by diverse sources, including user devices and non-human data generation sources. Gain insights into the challenges and methods for handling the massive volume of data on the Internet.