Case studies focused on business problems, tools, analysis process, and recommendations — without invented metrics.
Data AnalyticsSales data was fragmented across files and reports, making it hard to see performance clearly across channels, regions, and time.
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Analytics & VisualizationPatient-related datasets contained inconsistencies and were difficult to turn into clear classification insights and reusable reports.
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Business IntelligenceFinancial and commerce metrics lived in separate views, so pricing, channel, and performance decisions lacked a shared source of truth.
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AI / MLLearners were leaving courses before teams had a clear early signal to intervene.
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People AnalyticsAttrition risk was expensive and late — leaders needed earlier visibility into workforce signals.
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