Enterprise Analytics brings in external KPI targets to compare to production data through glide path. It also allows customization of date fields (if configured) and provides the ability to create global formulas. In addition several advanced features are available:
Forecasting
Feature: Forecast and predict data points in the future based on the current/past trend
Adding Forecasts to Widgets
Create a widget with one of the supported widget types (Line chart, Area chart, Column chart)
In the Data panel, place a time variable on the X-axis and the time-dependent variable that you want to forecast on the Y-axis
Click the “Owl” icon under the forecasted variable and select Forecast.
4. Toggle on the Visible control at the top of the Forecast Settings window to enable the forecast.
5. The read-only forecasted variable is the time-dependent variable that you selected. If you want to add an additional variable, add one in the Explaining Variable field this turn forecast into a multivariate forecast
6. In the Evaluation Period field, select whether you want to use all your past data for the forecast or only a recent period, and select the period.
7. If there is an evaluation period that should be ignored (for example - an unscheduled time period), this can be modified under the Evaluation Period drop down box.
The algorithm requires continuity in data - meaning we cannot exclude a time period in the middle of a time series.
The forecast period defines the number of values to predict.
The AI engine driving this type of forecast uses the following models:
Auto Arima
Prophet
Holt-Winters
Random Forest (Random Forest is only used in the ensemble approach; you cannot choose it manually)
These models can be modified in the forecast advanced settings.
To evaluate forecast accuracy:
Once the forecasted period is displayed in the widget, click Analyze It.
Select Forecast → Actual vs. Forecast. The comparison graph appears.
Forecasting Data Set Requirements:
Forecasting can be applied to the Line chart, Area chart, Column chart widget types
Forecasting requires at least 30 historical data points
Designers can add forecasting to widgets, Viewers can then use and customize definitions
Must be time based variable (with calendar icon) on the X-axis
NOTE - selections such as Date Picker or Shift Instance are not using a calendar type variable and would not be a valid forecasting X-axis selection
Y-axis must be a numerical value
Data cannot have Break-down selected
To learn more about how the Forecasting models work Click Here