Use forecasting in IBM® Cognos Analytics to discover and model trend, seasonality, and time dependence in data.

You can forecast in IBM Cognos Analytics by using automated tools that model time-dependent data. Automated model selection and tuning makes forecasting easy to use, even if you are not familiar with time series modeling.

Forecasts and their confidence bounds are displayed in visualizations as a continuation of historic data. You can also view the statistical details for generated models if you want to see the technical background.

Specifying time series in forecasts often requires data manipulation. Cognos Analytics supports a wide range of time series without the need for manipulation, ranging from standard date and time types, to nested periodic and cyclical time fields. When data is recognized as a time series, data preparation is automated. Appropriate trend and seasonal periods are detected, and models are selected from a set of nine different model types.

You can forecast in line, bar, and column visualizations. Forecasting allows analysis of hundreds of time series per visualization. Forecasts and confidence bounds are computed for each time series, and displayed in the visualization as extensions of the current data. You can inspect each time series separately, and tailor the forecast and results to your own data and requirements.

If you are familiar with forecasting models, you can view the selected model type, estimated model parameters, standard accuracy measures, and processing summary information.

Note: In Cognos Analytics 12.0.2 and earlier versions, the Forecast feature is not available in dashboards that are created from OLAP-sourced data modules, such as data modules created from Planning Analytics cubes. Only dashboards that are created from OLAP-sourced, enriched packages support forecasting in these versions of Cognos Analytics. For more information, see Creating an enriched package from a Planning Analytics cube.

Starting with Cognos Analytics 12.0.3, dashboards that are created from OLAP-sourced data modules support forecasting.