Learn how to ensure data consistency, which is a data quality dimension that refers to the degree of uniformity and compatibility of data across different sources, systems, or formats, and how it can affect the accuracy and reliability of CRM solutions.
Table of Contents
Question
Cloud Kicks wants to develop a solution to predict customers product interests based on historical data. The company found that employees from one region use a text field to capture the product category, while employees from all other locations use a plckllst. Which data quality dimension is affected in this scenario?
A. Completeness
B. Accuracy
C. Consistency
Answer
C. Consistency
Explanation
The correct answer is C. Consistency. Consistency is a data quality dimension that refers to the degree of uniformity and compatibility of data across different sources, systems, or formats. Consistent data follows the same rules, standards, and definitions, and does not have any conflicts, contradictions, or discrepancies.
Consistency can ensure data quality by facilitating data integration, analysis, and reporting, and by avoiding errors, confusion, or misinterpretation. Cloud Kicks wants to develop a solution to predict customers product interests based on historical data.
However, the company found that employees from one region use a text field to capture the product category, while employees from all other locations use a picklist. This affects the consistency of the data, as it creates different data types, formats, and values for the same attribute.
For example, a text field may allow free text input, such as “shoes”, “boots”, or “footwear”, while a picklist may have predefined values, such as “Footwear”, “Apparel”, or “Accessories”. This can make it difficult to compare, combine, or aggregate the data across different regions, and to generate accurate and reliable predictions of customers product interests.
Consistency is the data quality dimension that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Inconsistent data can cause confusion, errors, or duplication in data analysis and processing. For example, using different field types for the same attribute can affect the consistency of the data.
The latest Salesforce AI Associate actual real practice exam question and answer (Q&A) dumps are available free, helpful to pass the Salesforce AI Associate certificate exam and earn Salesforce AI Associate certification.