Case Study: Micron Technology cuts misprocessed-die identification from 7 days to under an hour with Cloudera

Leading the highly competitive memory & storage industry with data analytics and insight

Micron, a global leader in memory and storage solutions, faced a manufacturing and analytics challenge: its fabs generate petabytes of functional test data and trillions of measurements daily, and legacy systems added latency that slowed real‑time Hadoop analytics and prolonged defect identification (QA estimated up to seven days). The company needed a platform that let teams focus on analytics rather than data management and that could scale to address yield, cycle‑time, and ramp‑up improvements measured in fractions of a percent.

Micron deployed Hortonworks Data Platform (HDP) 3.0 with Apache NiFi for ingestion and SSD‑accelerated nodes, and used Hive for queries and analytics. The platform cut die‑identification time from seven days to under an hour, delivered a 2.5× performance gain versus HDD clusters, and scaled to support 100+ datasets, 100+ data scientists/engineers, ~1,000 users and 500,000 daily jobs—eliminating Hadoop latency and enabling faster insights to improve yield, cycle time, and product ramps.

Micron Technology

Greg Kincade

Senior Ecosystem Enablement Program Manager