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What Product Complaint Frequencies Reveal in Hadoop Analysis Projects?
Product-based complaint analysis in Hadoop Pig scripts reveals issue frequencies across categories, guiding quality fixes and inventory decisions—essential insight for Hive & Pig certification’s Customer Complaint project.
Question
What does analyzing complaints by product reveal?
A. Payment gateway errors
B. Marketing trends for each region
C. Frequency of issues across different product categories
D. Supplier reliability statistics
Answer
C. Frequency of issues across different product categories
Explanation
Analyzing complaints by product in the Customer Complaint project reveals the frequency of issues across different product categories through Pig GROUP BY operations on product fields within HDFS-stored complaint records, generating aggregated counts of defect reports, service failures, or quality problems per category like electronics, appliances, or clothing to pinpoint high-complaint SKUs or lines requiring immediate supplier audits, design revisions, or recalls. This product-level granularity exposes hidden patterns such as seasonal spikes in certain categories or correlations with specific batches, enabling data-driven inventory decisions, targeted quality control investments, and proactive customer communications that prevent widespread dissatisfaction and revenue loss from defective product lines dominating complaint volumes.