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Data dictionary

A table listing each data element with its name, data type, size or format, description and validation rule, so everyone uses the data the same way when coding and testing.

Part of: VCE Software Development - U3O1 - Programming — Module 10, VCE Software Development - U3O2 - Analysis and Design — Module 94, VCE Data Analytics - U3O1 - Data Analytics — Module 29, QCE Digital Solutions Unit 2 — Data-Driven Problems and Solution Requirements — Module 58, QCE Digital Solutions Unit 2 — Data and Programming Techniques — Module 23, QCE Digital Solutions Unit 2 — Prototype Data Solutions — Module 15, QCE Digital Solutions Unit 4 — Digital Methods for Exchanging Data — Module 123, WA Computer Science ATAR Year 11 — Modular Programming — Module 71, WA Computer Science ATAR Year 11 — Data Management — Module 39

Understanding Data dictionary in VCE Software Development U3O1

What it does: Recording the data type tells the programmer to store ticketPrice as a decimal number, not as text or an integer. A clear validation rule lets testers pick boundary values and invalid values to check that the program accepts and rejects data correctly. A data dictionary documents the data elements in a solution, usually with one row per variable or field. Each data element gets its own row so its details are easy to find and check. The validation column states the rules the data must meet, such as an allowed range. A name is made up of text, so it is stored as a string. Boolean is only for True/False values.

Common mistakes: The example must match the data type. An Integer field needs a whole number such as 15, not the word fifteen. Fix: Example: 15. A Boolean field can only hold True or False, so the example 25 does not match the data type or the format. Fix: Example: True.

Class: _____________________ · Name: _____________________ · Date: _________

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This module's key terms are also in a printable crossword (Modules 10–47) and word search (Modules 10–71).

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Learning

Duo

Which best describes a data dictionary?

A table documenting each data element's name, type, format, description and validationA list of Python keywords and what each one does

Matches

Name: x | Data type: Text | Description: (blank)

↓

The name is vague and the description is missing, so other developers cannot tell what the data element is for. Use a meaningful name like studentName and write a clear description.

Applying

Meanings

Term

data dictionary

Meaning

A table listing each data element with its name, data type, size or format, description and validation rule, so everyone uses the data the same way when coding and testing.

Practice

Name: studentAge

Testing

Gaps

Name | Data type | Example |

Check Answer

Spots

2Data type: Integer

3Example: fifteen

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Quick Questions

1. Which best describes a data dictionary?

A. A list of Python keywords and what each one does

B. A table documenting each data element's name, type, format, description and validation ✓

A data dictionary documents the data elements in a solution, usually with one row per variable or field.

2. In a data dictionary, how many rows are usually used for each variable or field?

A. One row per variable or field ✓

B. One row for all the variables together

Each data element gets its own row so its details are easy to find and check.

3. Which column would hold the value 'Must be between 0 and 100'?

A. Data type

B. Validation ✓

The validation column states the rules the data must meet, such as an allowed range.

4. Which data dictionary entry for a field called studentName has the correct data type?

A. studentName | String ✓

B. studentName | Boolean

A name is made up of text, so it is stored as a string. Boolean is only for True/False values.

5. Why do programmers and testers use a data dictionary?

A. So everyone uses and checks each piece of data the same way ✓

B. So the program runs faster on the computer

A data dictionary does not change speed. It gives developers and testers a shared description of the data, so they code and test consistently.

Match the Pairs

The data type column tells the programmer how to declare and store the value (text, whole number, decimal, date or Boolean) → Name: ticketPrice | Data type: Floating point

The validation column gives a rule that supports testing, because testers can build test data that passes and fails it → Validation: Range 0 to 100 | Test with 0, 100, -1, 101

Name: x | Data type: Text | Description: (blank) → The name is vague and the description is missing, so other developers cannot tell what the data element is for. Use a meaningful name like studentName and write a clear description.

Name: quantity | Data type: Integer | Example: 2.5 → The example value is a decimal, but the data type is Integer. The example must match the data type, for example 3.

Key Term

data dictionary

A table listing each data element with its name, data type, size or format, description and validation rule, so everyone uses the data the same way when coding and testing.

Fill in the Blanks

1. Name | Data type | Example | Validation

Hint: Type the column heading that holds the rule used to check each entry.

2. Name: studentAge Data type: Integer Validation: range 12 to 18

Hint: Type the data type for a whole-number age.

3. Name: dateOfBirth Format: DD/MM/YYYY Example: 25/03/2008

Hint: Type the date format that matches the example shown, day first.

4. Name: password Data type: String Validation: length >= 8

Hint: Type the comparison operator meaning 'at least'.

5. Name: postcode Size: 4 characters Example: 3000

Hint: Type the number of characters in the example value.

Spot the Error

Question 1

A Name: studentAge

B Data type: Integer

C Example: fifteen

D Validation: 5 to 18

Line C — The example must match the data type. An Integer field needs a whole number such as 15, not the word fifteen. Fix: Example: 15

Question 2

A Name: isEnrolled

B Data type: Boolean

C Format: True or False

D Example: 25

Line D — A Boolean field can only hold True or False, so the example 25 does not match the data type or the format. Fix: Example: True

Question 3

A Name: postcode

B Data type: String

C Format: 4 digits

D Validation: must be 4 letters

E Example: 3000

Line D — The validation rule contradicts the format. The format says 4 digits, so the rule should check the length is 4, not that it is made of letters. Fix: Validation: length must be 4

Question 4

A # age: Integer, 5 to 18

B age = int(input('Age: '))

C if age > 5 or age < 18:

D print('Invalid age')

Line C — The data dictionary says age must be 5 to 18. The invalid test must catch values below 5 or above 18, so the operators are the wrong way round. Fix: if age < 5 or age > 18:

Question 5

A Name | Type | Example

B score | Integer | 87.5

C price | Float | 4.50

D isPaid | Boolean | True

Line B — The score is listed as an Integer, so its example must be a whole number. 87.5 is a floating point value. Fix: score | Integer | 87

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