This report provides a comprehensive overview of business analytics and intelligence. It begins with defining business analytics, exploring various tools like R, Tableau Public, Python, SAS, and Apache Spark, and then delves into techniques such as SWOT, MOST, and PESTEL analysis. The report further analyzes marketing analytics, including demand functions, revenue, cost, and profit optimization for a new product. It determines the optimal price and demand, and explores the impact of unit costs on profitability. Finally, the report examines forecasting techniques, using the exponential smoothing method with varying damping factors (0.3, 0.4, 0.5, and 0.6) to forecast monthly sales. It includes a comparison of actual and forecasted sales, along with error analysis using MAD, MSE, and MAPE, providing insights into the accuracy of the forecasting models.
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