Data, Information, and Metadata Concepts

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58 question-and-answer flashcards covering structured vs. unstructured data, data vs. information, multimedia databases, metadata properties, and quadratic-equation basics.

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58 Terms

1
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What type of data does a small business owner's customer contact database (names, addresses, phone numbers) represent?

Structured data (organized in a tabular form with specific data types).

2
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Which statement best describes structured data?

Data stored in a tabular form, including numeric, character, and date data types.

3
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Why is the small business owner’s customer database considered structured?

Because it is stored in a tabular form with specific data types like names, addresses, and phone numbers.

4
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How many bytes are in one petabyte (PB)?

10^15 bytes.

5
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How many bytes are in 3 petabytes?

3 × 10^15 bytes.

6
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A database includes a photo image, a sound recording, and a scanned image. What types of data are these?

Multimedia data consisting of a photo image, sound recording, and scanned image.

7
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Do multimedia data types such as images, audio, and scans fit into traditional tabular forms?

No, they do not fit into traditional tabular forms.

8
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What type of data includes multimedia elements such as images, sound, and video?

Unstructured data.

9
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A database containing a photo image, sound recording, and scanned image is an example of which data category?

Unstructured data.

10
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What is the traditional definition of data?

Facts concerning objects and events that could be recorded and stored on computer media.

11
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When a repair shop combines structured customer data with multimedia images, what types of data are involved?

Both structured and multimedia data.

12
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What is the result of combining structured data with multimedia data in a database?

A true multimedia environment.

13
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How many terabytes are in 3 petabytes?

3000 TB.

14
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Why might a several-terabyte database contribute to complexity?

Because very large data volumes often involve complex data management and processing.

15
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Why does variety of data add complexity to decision-support databases?

They require sophisticated analysis and integration of various data types.

16
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Considering size and variety, why is a multi-terabyte decision-support database complex?

The combination of large size and the need for complex data analysis makes it complex.

17
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Are the raw facts “Smith, John A. – 123456789” processed or contextualized?

No, they are raw and unprocessed.

18
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Do such raw lists of facts increase a user’s knowledge?

No, they do not increase knowledge.

19
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Are unprocessed lists of names and numbers considered data or information?

Data.

20
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What is the first step in transforming raw facts into information?

Identify the raw data provided.

21
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What context could convert the list of names and IDs into information?

Indicating that it is a class roster for a particular course.

22
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Which structured presentation of the data increases user knowledge?

“Brown, Alice M. – Student ID: 112233445; Green, Bob C. – Student ID: 556677889.”

23
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If Course A has 30 students, Course B 25, and Course C 40, what is total enrollment?

95 students.

24
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Which course has the highest enrollment?

Course C.

25
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Which graphical representation best summarizes the enrollment data?

A bar chart.

26
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What might be a potential need for Course C given its highest enrollment?

Additional resources or faculty.

27
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Given student data without course names, what additional item is needed for instructor usefulness?

Course names.

28
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Which option correctly adds context and structure to the student data?

“Wilson, Emma J. – Student ID: 334455667 – Course: Math 101; Thompson, David K. – Student ID: 998877665 – Course: Physics 202.”

29
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Dr. Smith teaches 3 courses, Dr. Johnson 2, Dr. Lee 4. What is total number of courses?

9.

30
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Which faculty member has the highest workload?

Dr. Lee.

31
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What percentage of the courses does Dr. Johnson teach?

22.22 %.

32
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What is an appropriate summary statement of the faculty workload data?

Dr. Lee has the highest workload among 3 instructors teaching a total of 9 courses.

33
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What is the quadratic formula for solving ax^2 + bx + c = 0?

x = (−b ± √(b^2 − 4ac)) / (2a).

34
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For 2x^2 − 4x − 6 = 0, what is the discriminant?

64.

35
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What are the roots of 2x^2 − 4x − 6 = 0?

x = 3 and x = −1.

36
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What is the sum of the roots of 2x^2 − 4x − 6 = 0?

2.

37
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What is the product of the roots of 2x^2 − 4x − 6 = 0?

−3.

38
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In metadata, what is the correct length property for the data item “Student Name”?

50.

39
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For “Course Code” metadata, what is the correct source property?

Academic Unit.

40
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For “Student Name” metadata, what is the correct description property?

Full name of the student.

41
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For “Course Code” metadata, what is the correct data type?

Alphanumeric.

42
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In the “Student ID” metadata example, which property is missing/inconsistent?

Min value.

43
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In the “GPA” metadata example, which property is missing or inconsistent?

None (all required properties are present).

44
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Which GPA value is inconsistent with metadata (Decimal 0.0–4.0)?

4.5.

45
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Which Student ID value is inconsistent with metadata (Integer length 9)?

12345678 (only 8 digits).

46
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Which definition correctly specifies metadata for “Course Title”?

Name: Course Title, Type: Alphanumeric, Length: 100, Description: The title of the course, Source: Academic Unit.

47
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Which definition correctly specifies metadata for “Enrollment Count”?

Name: Enrollment Count, Type: Integer, Length: 3, Min: 0, Max: 999, Description: Number of students enrolled in the course, Source: Registrar.

48
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What is the data type of the “Major” item in the class roster metadata?

Alphanumeric.

49
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What is the length of the “Major” data item?

4.

50
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What is the description of the “Major” data item?

Student major.

51
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What is the source of the “Major” data item?

Student Information System.

52
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Why is managing metadata crucial for database designers and users?

It provides essential context about data, including source, meaning, and usage.

53
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How does metadata help avoid data misinterpretation?

By distinguishing between similar data items and ensuring correct interpretation.

54
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What best describes metadata?

Data about data.

55
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Which is an example of descriptive metadata?

File title.

56
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Which type of metadata is used to manage and control data?

Administrative metadata.

57
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What is the primary purpose of structural metadata?

To provide information about the format and structure of data files.

58
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Which of the following is NOT a common use of metadata?

Increasing data redundancy.