Which Inconsistency Appears in the January Sales Table?
A sales analyst is using the following table to produce a report on January sales data:
Which of the following inconsistencies is present in the data set?
Community Insight
The question tests recognition of data-quality defects in a live table, and the trap is confusing record-level duplication with attribute-level redundancy or with blank/incomplete fields.
This DA0-002 data-quality question shows a January sales table and asks which inconsistency it contains, with duplication, redundancy, missing values and outliers as the choices. The exhibit contains repeated rows, so duplication (A) is the inconsistency present in the data set.
Option C (missing values) is the most common wrong pick, because learners assume a blank or incomplete cell must be shown; the exhibit instead repeats complete records, and missing values would appear as empty required fields.
Community Discussion (2 comments)
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Expert Analysis
Why the Answer Is Correct
Duplication means the identical record appears more than once in the same table, and the January sales exhibit repeats a row rather than presenting each transaction uniquely. Because the repeated row carries the full set of values (date, product, representative, amount), every column is populated — the flaw is that a single sale is represented twice. In a sales report this inflates January totals through double counting, which is exactly the inconsistency an analyst must flag before publishing. Detecting it is straightforward: sort or group by a transaction-level key and look for records that share identical values across all fields. This fits the exhibit's repeated rows, so duplication (A) is the correct answer.Why the Other Options Are Wrong
Redundancy (B) describes the same information stored in multiple places across different tables or columns — a database design issue, not a repeated record inside one table. Missing values (C) would appear as blank, null or placeholder cells in required fields such as an empty sales amount or an absent date; the exhibit's fields are filled in. Outliers (D) are extreme but valid observations that fall far from the rest of the distribution, and nothing in a January sales table of this kind is being flagged as an anomalously high or low figure. Anomalies and blanks are different defect classes, and neither is what the shown rows demonstrate.Community Comment Notes
FaisalRifat selected option A and characterized duplication as "The same records repeated in a data set", which matches the repeated-row pattern in the exhibit. Amelia233 argued the opposite, marking A wrong and claiming "some fields that should contain information are blank or incomplete" while awarding the check to missing values. That disagreement is the typical split on this item: learners who read the table as showing gaps choose C, while those who spot the identical repeated record choose A. Reading the exhibit row by row for a fully identical match is the reliable way to settle it.Official Reference
Exam Strategy
Before choosing, scan the table column by column: blank cells point to missing values, extreme figures to outliers, and a row whose values match another row exactly to duplication. Eliminate redundancy immediately unless the same attribute is repeated across different columns or tables.
Frequently Asked Questions
Why is missing values (C) wrong when the table looks incomplete?
Missing values require actual blank or null cells in required fields; here every field is populated and the defect is an identical repeated row.
What is the difference between duplication and redundancy here?
Duplication repeats whole records inside one table, while redundancy stores the same attribute in multiple columns or tables — only repeated records appear in this exhibit.
Related Analysis
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