Data Science Lecture 1 Quiz
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Questions and Answers

What percentage of the total grade is allocated to the final exam?

  • 20
  • 50 (correct)
  • 10
  • 25

Which of the following elements is not categorized as operational data?

  • Macroeconomic data (correct)
  • Inventory
  • Payroll
  • Sales

What is the purpose of data mining?

  • To store data in warehouses
  • To analyze and convert data into useful information (correct)
  • To enhance graphical user interfaces
  • To perform statistical modeling only

Which of the following is considered metadata?

<p>Database design definitions (D)</p> Signup and view all the answers

What is the primary distinction between data and information?

<p>Information arises from patterns and relationships in data. (D)</p> Signup and view all the answers

In the context of data warehouses, what does OLAP stand for?

<p>Online Analytical Processing (A)</p> Signup and view all the answers

Which of the following is an example of pattern matching?

<p>XML/RDF searching (D)</p> Signup and view all the answers

What can information analysis of retail sales data help determine?

<p>Customer preferences in product categories (A)</p> Signup and view all the answers

Flashcards

Data

Facts, numbers, or text processed by a computer.

Information

Relationships or patterns among data.

Knowledge

Understanding of historical patterns and future trends.

Data Warehousing

Storing and managing large amounts of data.

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OLAP

Analysis of data stored in a warehouse

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Data Mining

Discovering patterns and relationships within data.

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Keyword Search

Finding data based on specific words.

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Pattern Matching

Finding patterns in data (e.g., XML/RDF).

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Study Notes

Course Information

  • Course: Data Science
  • University: Alexandria University
  • Lecture: 1

Grading Breakdown

  • Assignment 1: 2.5 points, Week 4
  • Quiz 1: 2.5 points, Week 6
  • Midterm Exam: 20 points, Week 8
  • Assignment 2: 2.5 points, Week 11
  • Quiz 2: 2.5 points, Week 12
  • Practical Exam: 10 points, Week 14
  • Final Project: 10 points, Week 14
  • Final Exam: 50 points, Week 15-16
  • Total Points: 100

Data in the Modern Era

  • Data is abundant, organizations collect vast amounts of data
  • Data exists in varied formats and databases

Data Types

  • Operational/Transactional Data: Sales, costs, inventory, payroll, accounting
  • Non-Operational Data: Industry sales, forecasts, macroeconomic data
  • Meta Data: Data about the data itself, like database design, data dictionary definitions

Data Analysis and Processing

  • Data warehouse and OLAP
  • Indexing, Searching, and Querying
  • Keyword-based searches
  • Pattern matching (e.g., XML/RDF)
  • Knowledge discovery
  • Data mining
  • Statistical modeling

Data and its Transformation

  • Data is the new oil, signifying its crucial role
  • The vast quantity of data, combined with advances in technology, is revolutionizing many aspects of modern life

Cognitive Computing

  • Humans expect systems to emulate human behavior
  • Systems should adapt to changes in information and goals
  • Systems need to be interactive, smoothly engaging with other systems and humans
  • Systems need to understand context to extract deeper meaning and use multiple information sources

More Data About Cognitive Computing

  • Processing large uncertain data sets (text, speech, sensors, images)

Examples of Data Usage

  • Streaming an episode of Game of Thrones (2.8 GB of data)
  • Listening to music (40 MB)
  • Using Instagram (100 MB)
  • Keeping up with a television show (1.4 GB)

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Description

Test your knowledge on the fundamentals of Data Science as covered in Lecture 1. This quiz focuses on data types, data analysis, and processing methods essential for understanding data in the modern era. Perfect for students at Alexandria University.

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