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QCE Digital Solutions Unit 2 · Modules 144–185

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A free printable QCE Digital Solutions Unit 2 definitions worksheet with 10 key terms, built from the key terms of Data and Programming Techniques (Modules 144–185) — Programming requirements: SQL and algorithms, System requirements: platforms, System requirements: hardware, Data acquisition, Data completeness, Data consistency and more. Print it or save it as a PDF — the answer key starts on its own page. No login needed.

QCE Digital Solutions Unit 2 Definitions Worksheet: Data and Programming Techniques (Modules 144–185)

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Date:
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Key terms

Write what each term means, in your own words.

1
programming requirements
2
platform requirement
3
hardware requirement
4
data acquisition
5
data completeness
6
data consistency
7
insertion anomaly
8
update anomaly
9
deletion anomaly
10
Integrity

Answer Key

QCE Digital Solutions Unit 2 · Modules 144–185 · Student wording will vary for definitions
1programming requirements — The list of SQL statements and algorithms a data-driven solution must include so it can carry out each of its functions, with each requirement linked to a task.
2platform requirement — A requirement stating the operating system, device type or environment (desktop, web, mobile, database software) that the solution must run on.
3hardware requirement — The processing power, memory, storage and peripherals needed to run a solution and hold its data, such as disk space for a database or RAM for large files.
4data acquisition — Capturing data from a source and bringing it into a solution in a usable form: choose the source, capture it accurately, then check it on arrival.
5data completeness — Data is complete when every required value is present, with no missing fields or records. A presence check finds blank required fields.
6data consistency — The same fact has the same value and format everywhere it is stored, with no spelling variations or conflicting copies. Storing each fact in one place helps keep it consistent.
7insertion anomaly — A problem where a new fact, like a new course, cannot be stored until unrelated data, like a student, exists, forcing null values or dummy rows in a single table.
8update anomaly — A problem where a repeated fact is changed in one row but not its other copies, so the data disagrees. Caused by redundancy, and fixed by normalisation.
9deletion anomaly — Deleting a row also wipes out a separate fact stored only in that row, e.g. deleting the last student enrolled in a course also erases the course details.
10Integrity — Data stays accurate and unaltered unless an authorised person changes it, so a tampered bank balance breaks integrity.

Modules this definitions worksheet covers

Every module has its own free printable worksheet with an answer key, and students can practise the same terms interactively on Cloodit.

Part of: QCE Digital Solutions Unit 2 — Data and Programming Techniques

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