ML-powered forecasting - Amazon QuickSight

Important: We've redesigned the Amazon QuickSight analysis workspace. You might encounter screenshots or procedural text that doesn't reflect the new look in the QuickSight console. We're in the process of updating screenshots and procedural text.

To find a feature or item, use the Quick search bar.

For more information on QuickSight's new look, see Introducing new analysis experience on Amazon QuickSight.

ML-powered forecasting

The ML-powered forecast computation forecasts future metrics based on patterns of previous metrics by seasonality. For example, you can create a computation to forecast total revenue for the next six months.

To use this function, you need at least one dimension in the Time field well.

For more information about working with forecasts, see Forecasting and creating what-if scenarios with Amazon QuickSight.

Parameters

name

A unique descriptive name that you assign or change. A name is assigned if you don't create your own. You can edit this later.

Date

The date dimension that you want to rank.

Value

The aggregated measure that the computation is based on.

Periods forward

The number of time periods in the future that you want to forecast. Ranges from 1 to 1,000.

Periods backward

The number of time periods in the past that you want to base your forecast on. Ranges from 0 to 1,000.

Seasonality

The number of seasons included in the calendar year. The default setting, automatic detects this for you. Ranges from 1 to 180.

Computation outputs

Each function generates a set of output parameters. You can add these outputs to the autonarrative to customize what it displays. You can also add your own custom text.

To locate the output parameters, open the Computations tab on the right, and locate the computation that you want to use. The names of the computations come from the name you provide when you create the insight. Choose the output parameter by clicking on it only once. If you click twice, you add the same output twice. Items displayed in bold can be used in the narrative.

  • timeField – From the Time field well.

    • name – The formatted display name of the field.

    • timeGranularity – The time field granularity (DAY, YEAR, and so on).

  • metricField – From the Values field well.

    • name – The formatted display name of the field.

    • aggregationFunction – The aggregation used for the metric (SUM, AVG, and so on).

  • metricValue – The value in the metric dimension.

    • value – The raw value.

    • formattedValue – The value formatted by the metric field.

    • formattedAbsoluteValue – The absolute value formatted by the metric field.

  • timeValue – The value in the date dimension.

    • value – The raw value.

    • formattedValue – The value formatted by the date field.

  • relativePeriodsToForecast – The relative number of periods between latest datetime record and last forecast record.