In part 1 we introduced a manufacturing company that’s seeking to improve their market predictions. Due to the cost of shipping products, the company needs to accurately predict demand two months into the future. After trying several data transformations, we found the data may still be non-stationary (have seasonal or other trends). We tried using […]
Predict product demand using ARIMA forecasting models and identifying trend and seasonality components in time series data.
Monte Carlo Simulation is an important tool used to factor in unknown variables and random events which can compound, giving scientists the ability to make better long term predictions when traditional models are inapplicable.
Having knowledge of how a leader perceives both the operations and the goals of the organization are critical for a business intelligence analyst. In order to successfully apply Goal Question Metrics (GQM) analyst’s needs to have a thorough understanding of the processes and objectives of both the team and management, as well as the technical analytical skills to be able to measure progress against these processes and objectives.
The four disciplines of analytics–Descriptive, Diagnostic, Predictive, Prescriptive–contribute to the goal of improving our business using our own data. In this article we look at some of the common questions each of the disciplines help us answer.
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