Case Study: USDA National Agricultural Statistics Service (NASS) achieves faster, more accurate national agricultural estimates and anomaly detection with SAS Enterprise Miner

USDA's NASS collects, summarizes hundreds of data series about the nation's crops, livestock

The USDA’s National Agricultural Statistics Service (NASS) is the nation’s primary source for hundreds of crop- and livestock-related data series—covering more than 120 crops and dozens of livestock estimates—used daily by economists, producers, insurers, traders and government officials. NASS must capture, edit, summarize and report vast volumes of survey data from 45 field offices on tight timelines while detecting anomalies and ensuring the accuracy of mission‑critical economic indicators.

NASS uses SAS (including SAS Enterprise Miner) to aggregate survey data from Sybase/Redbrick, provide state-level point‑and‑click routines for review and editing, and run mainframe validations that surface anomalies before national aggregation. The result is faster, more reliable data cleaning and reporting, leading to accurate national summaries and economic forecasts that better support business and government decisions.

USDA National Agricultural Statistics Service

Dave Aune

Chief, Statistical Methods Branch