Nischith R completed Data Analytics and AI

Built an end-to-end demand forecasting workflow on 9,648 historical transactions: performed EDA across sales, regions, products, and channels; decomposed the monthly series to inspect trend and seasonality; and compared a moving-average baseline, linear regression, and SARIMA using a proper chronological split. SARIMA delivered the strongest holdout performance, reducing forecast error versus simpler approaches and supporting peak-season planning.

• Leakage-Free Time-Series Splitting
• Comparative Forecast Evaluation
• Seasonality and Trend Detection