Power BI AI Visualizations: Predict Future Values for Time Series Data with Line Chart forecasting

Forecasting is a form of machine learning that predicts future events using historical data. Power BI offers an automatic forecasting feature based on exponential smoothing models for generating forecasts from line charts with date/time or uniformly increasing whole number values on the x-axis. Users can add a forecast by clicking on the Analytics tab and entering arguments for forecast length, confidence interval, and seasonality. The forecasting feature generates three values, forecast value, upper bound, and lower bound, with a grey range that represents 95% confidence intervals for each future month. To ensure accuracy, users can compare the forecast with actual data by trying hindcasting and modifying the "ignore last" option. Good quality time series data for forecasting should have a long enough historical period on the time dimension and little to no missing data, with a trend and seasonality pattern. To use the Power BI forecasting feature, users need to select an appropriate historical period and configure forecasting options based on their needs.
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