What factors are contributing to the increased error rate in Precisely's Data360 Govern data quality checks this month?

Introduction

The increased error rate in Precisely's Data360 Govern data quality checks this month is a critical issue that requires immediate attention. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term implications for our data governance platform.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a recent change in our data processing pipeline. Have there been any updates to our ETL processes or data sources in the past month?

Why it matters: Recent changes often correlate with performance shifts. Expected answer: Yes, there was a minor update to our ETL process. Impact on approach: If confirmed, we'd focus on the specific changes made.

• Considering user segments, I'm wondering if this issue is affecting all customers equally. Are we seeing a higher error rate across the board, or is it concentrated in specific industries or data types?

Why it matters: Helps narrow down potential causes and prioritize our response. Expected answer: The issue seems more prevalent in financial sector clients. Impact on approach: We'd investigate industry-specific data patterns or regulations.

• Given the nature of data quality checks, I'm curious about the types of errors we're seeing. Has there been a shift in the distribution of error types (e.g., more formatting errors vs. completeness issues)?

Why it matters: Different error types point to different root causes. Expected answer: There's been an increase in data format inconsistencies. Impact on approach: We'd focus on data standardization processes and input validation.

• Thinking about system health, I'm concerned about potential infrastructure issues. Have we observed any changes in system performance or resource utilization coinciding with the increased error rate?

Why it matters: Infrastructure problems can manifest as data quality issues. Expected answer: No significant changes in system performance metrics. Impact on approach: We'd shift focus from infrastructure to data processing logic.