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Answer: Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop machine learning analysis of metrics
The question focuses on reducing the 3-week aggregate reporting time to decrease customer wait time for parts. Option C is optimal because: (1) Increasing cellular connectivity from the current ~1% (200K out of 20M vehicles) to 80% ensures real-time data collection from most vehicles, directly addressing data freshness issues (currently, data is only collected during maintenance). (2) Migrating from FTP to streaming transport (e.g., Pub/Sub) eliminates batch processing delays, enabling near-real-time data ingestion. (3) Machine learning analysis leverages the fresher data for predictive maintenance, reducing downtime. Community discussion shows strong support for C, with high-upvote comments (e.g., 37 upvotes) citing official Google practice exams and emphasizing that cellular connectivity and streaming are critical for data freshness, while format changes (e.g., CSV to binary in B) are less impactful. Options A and D are suboptimal due to SFTP (still batch-oriented), and B's format change offers marginal benefits compared to the transformative impact of increased connectivity in C.
Author: LeetQuiz Editorial Team
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You have analyzed TerramEarth's business requirements and determined that reducing customer wait time for parts will achieve the most significant reduction in downtime. To focus on decreasing the current three-week aggregate reporting time, what process modifications should you recommend?
A
Migrate from CSV to binary format, migrate from FTP to SFTP transport, and develop machine learning analysis of metrics
B
Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine learning analysis of metrics
C
Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop machine learning analysis of metrics
D
Migrate from FTP to SFTP transport, develop machine learning analysis of metrics, and increase dealer local inventory by a fixed factor
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