Why has Matillion's data transformation job execution time increased by 30% over the past month?

Introduction

Matillion's data transformation job execution time increase of 30% over the past month is a critical issue that demands immediate attention. This performance degradation could significantly impact user satisfaction, operational efficiency, and ultimately, the company's bottom line. I'll approach this problem systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent product update. Has there been any significant change to Matillion's data transformation features in the last 1-2 months?

Why it matters: Recent changes could directly impact performance. Expected answer: Yes, there was a major update. Impact on approach: If yes, we'd focus on the new features or changes.

• Considering the scale of the issue, I'm wondering about the affected user base. Is this 30% increase consistent across all users, or are certain segments more affected?

Why it matters: Helps identify if it's a global issue or specific to certain use cases. Expected answer: It varies across user segments. Impact on approach: If varied, we'd prioritize investigating the most affected segments.

• Given the nature of data transformation jobs, I'm curious about the data volumes. Has there been any significant change in the average size or complexity of data sets being processed?

Why it matters: Increased data volume or complexity could explain longer execution times. Expected answer: Data volumes have remained relatively stable. Impact on approach: If stable, we'd focus more on internal system issues rather than data characteristics.

• Thinking about system health, I'm concerned about potential infrastructure changes. Have there been any recent modifications to the underlying infrastructure or cloud resources?

Why it matters: Infrastructure changes could impact processing power and efficiency. Expected answer: No major infrastructure changes. Impact on approach: If no changes, we'd look more closely at software-level issues.