Data entry controls: to reduce transcription and transposition errors during data entry, the system analyst should provide which controls?

Introduction / Context:
Transcription (mis-keying) and transposition (digit order swap) errors are common during manual data entry. Robust input controls catch these early to avoid costly downstream corrections. System analysts specify preventive and detective controls, many of which are simple to implement and highly effective when used together.

Given Data / Assumptions:

• We are addressing batch and online entry scenarios.
• Controls can be applied at field, record, and batch levels.
• The aim is detection, not necessarily automatic correction.

Concept / Approach:
Check digits add a mathematically derived digit to identifiers (e.g., mod-11 or Luhn algorithm) that detects single-digit errors and many transpositions. Hash totals are non-meaningful sums (or hashed sums) of key fields across a batch, allowing verification that all items were captured correctly. Batch totals compare control totals (e.g., count, amount, hash) from source documents to system totals after entry. Together, these create layered defenses against input errors that might otherwise slip through and corrupt master data or financial statements.

Step-by-Step Solution:

Verification / Alternative check:
Auditing and AIS literature recommends combining field-level validation (check digits) with batch control totals to achieve high detection rates of entry errors.

Why Other Options Are Wrong:

• Any single control alone leaves gaps; layered controls are stronger.
• None: incorrect because all listed controls are textbook solutions.

Common Pitfalls:
Using only a check digit and omitting batch reconciliation; or relying on batch totals without field-level validations, reducing coverage of certain error patterns.

Final Answer:
All of the above