Validation

Question

Validation

BlackTom AI · Accepted Answer

Validation checks compare user input against predefined rules (format, type, range, presence) to catch and block incorrect entries before they are stored.

1. Relevant knowledge points and concepts
- Data validation: automated checks that enforce rules (e.g., numeric-only, date format, value ranges, required fields, lookup lists).
- Purpose: reduce errors at capture time so stored data is more reliable.
- Limitations: validation lowers the probability of bad data but cannot guarantee 100% accuracy (human error, incorrect but rule-compliant values, or subsequent data corruption remain possible).

2. Step‑by‑step reasoning
- If a field requires an integer between 1 and 100, a validation rule rejects "abc", "150", or "12.3". That prevents those inaccurate inputs.
- Validation can enforce formats (email@example.com), required completion, or cross-field consistency (end date after start date). Each rule filters out a subset of invalid inputs.
- Because validation blocks or warns on invalid entries, the overall chance of inaccurate data being entered is lowered.

3. Calculations / intermediate steps
- No numeric calculations are necessary; the logical flow is: rule exists → invalid input detected → input rejected or corrected → fewer invalid records saved.

4. Why the correct answer is correct
- Option c (“reduces the chance of inaccurate data being input”) matches the standard definition and effect of validation: it diminishes the likelihood of incorrect data entering the system by catching violations of rules at entry time.

5. Why the other options are incorrect
- a (“ensures all data is accurate”): too strong — validation reduces errors but cannot guarantee all data is accurate (e.g., wrong but rule-compliant values).
- b (“increases the chance of inaccurate data being input”): opposite of truth; validation is designed to reduce, not increase, inaccurate inputs.
- d (“ensures that all data is inaccurate”): nonsensical and incorrect.

6. Conclusion
Validation reduces the chance of inaccurate data being input; therefore the correct answer is c.

Validation单项选择题

类似问题

What challenges might arise from not performing data validation?

In the process of cleaning data, what types of data validation would be imperative? (Select all that apply)

Which of the following are examples of consistency checks in data validation?

Which of the following are important considerations when defining data validation rules?

Why is it important to perform null checks during data validation?

What is a key activity during the Creation stage?

What is the purpose of validating the data at the end of the cleaning process?

Which of the following are advisable strategies when working with datasets? (Multiple answers possible).

更多留学生实用工具

智能学习助手

风格化写作助手

论文查重助手

文献引用助手

课堂转译助手

课堂笔记助手

Quiz搜索助手

学校历年真题

智能刷题助手

智能匹配练习

希望你的学习变得更简单