U2T2 - Data + Information Flashcards Preview

CCEA AS Digital Technology > U2T2 - Data + Information > Flashcards

Flashcards in U2T2 - Data + Information Deck (38)
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1

What is data?

Raw facts + figures which are out of context + therefore meaningless. A random set of digits.

2

What is information?

Raw facts and figures that are processed + have context and therefore meaning.

3

What is knowledge?

Understanding + consequences placed on information.

4

What are the 6 terms that we need to decipher high quality info from low quality info?

Accurate, Up to Date, Relevant, Complete, Effectively presented + reliable.

5

How might inaccurate data occur?

Poorly worded questions which lead to inaccurate answers, not enough sources, manual data entering mistakes, incorrectly calibrated instruments. E.g. Transcription error.

6

Why is up to date data so important for information quality?

Can be misleading or incorrect as information changes over time e.g. Change of address

7

Why is relevant data so important for high quality information?

It cannot be useful if it is irrelevant. E.g. Unnecessary details.

8

Why is complete data so important for information quality?

If part of info is missing, you cannot fully understand and take in the whole picture. E.g. A field is left out.

9

Why is effectively presented data so important for information quality?

If it is disorganised it is hard to understand and so becomes less useful. e.g alphabetical order for class lists.

10

Why is reliable data so important for information quality?

Sources that aren't reliable can be prone to error so may be inaccurate and therefore low quality.

11

What is verification?

Use of checks to ensure data is high quality + accurate. It confirms the integrity of the data as it's copied between diff parts of computer system.

12

What can verification be used for?

Ensure data in database contains no mistakes when transferring data from original source.

13

When can verification take place?

When data is entered at the human-machine interface + when copied between other components within computerised system.

14

Explain the purpose of a key field?

To be unique to only one data subject so it distinguishes from others + also provides a link between tables.

15

Explain how a check digit can be used to detect a transposition error?

When the product code is entered, the system calculates the check digit + ensures they are both the same. If not, an error is flagged. A transposition error is when the places of 2 digits are interchanged. The weightings will not be accurate for each number in the code so the check digits will not match.

16

3 examples of data verification?

Double entry, proof reading + check digits.

17

Describe double entry verification.

The field must be entered twice to ensure that the typist has not made a mistake. E.g transposition. If not matched, an error is flagged.

18

Describe proof reading verification.

You must read over the data and confirm it is accurate before confirming it.

19

Describe check digit verification.

Extra digits added to a number code. They are worked out by modulus 11 arithmetic and reduce errors. E.g. Transposition.

20

How might you calculate a check digit? E.g. 1234x

1234 - product code
5432 - weightings
30 - total
2r8 - /11
11 - 8 = 3 (Check digit)

21

What 2 extra errors might occur in batch processing?

A document may be missed out or the data on the document may be entered twice.

22

What is batch processing?

Entering a large number of documents at once e.g. Using a scanner.

23

What is a batch total?

Total value of 1+ fields in a data batch. Calculated manually + then checked with computer total. E.g. Number of documents.

24

What are control totals?

Batch totals with a meaningful value e.g. Number of documents or transactions.

25

What are hash totals?

Batch totals with no meaning. E.g. Total of all numeric fields for a certain record (employee number)

26

What can hash totals be used to spot?

Missed or doubly entered documents, one document entered twice whilst one missed.

27

What is data validation?

Automatic checking of data entered into computer system to reduce errors. Sensible, reasonable, within suitable boundaries + complete.

28

Examples of validation checks?

Range, presence, length, format, type, lookup, check digit.

29

What is a range check?

Rejects data outside 2 limits. E.g. Age 11 to 18. Error is flagged if not between these.

30

What is a presence check?

Ensures no fields are missed out when entering data, and error is flagged if data is missing. E.g. No name