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Production data generated by modern businesssystems—including manufacturing sensors, operationaldatabases, healthcare records, retail transactions, andagricultural monitoring—remains critically underutilizeddue to three primary barriers: expensive businessintelligence platforms, specialized data science expertiserequirements, and extensive configuration overhead(weeks to months). This paper presents a universal AIoptimized production data analyzer that eliminates thesebarriers through automated intelligence and zeroconfiguration deployment. Experimental validation acrossmanufacturing, business operations, healthcare, retail, andagriculture datasets (ranging from 500 to 50,000+ records)demonstrates: automatic dashboard generation in 3seconds versus weeks for conventional BI tools, naturallanguage query response latency of 2-5 seconds, and 92%average data quality assessment accuracy. Bydemocratizing enterprise-grade analytics, this frameworkprovides capabilities equivalent to a 24/7 junior dataanalyst at zero marginal cost, addressing the criticalanalytics gap faced by small and medium enterprises.
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DAS et al. (2026) studied this question.
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