AI Transform for Jedox Cloud


With the AI Transform, you can use AIssisted™ Planning functionality within Jedox Integrator.

Note: the AI Transform is available through Jedox Cloud only and requires a license. Contact your Jedox Sales representative for more information.

Main Settings

The name of the measure dimension where you would like the prediction values stored.

Input source

Input source is an extract containing Time, Version, and Measure dimensions. Note: do not use the same source for both input and export, as the input data may be replaced if the transform is followed by a cube load.  See the sample input and output source data previews for examples.

Time, Version, and Measures dimensions

The drop-down lists contain column names from the input source. Time, Version, and Measure dimensions can have variable or constant inputs.


The Values column from the time series input source.


Time Series Forecasting is the only function at this time. Additional AI functions will be available in an upcoming release.


Inputs for Time Series Forecasting must have a period assigned. Period can be Daily (365), Monthly (12), Weekly (52), and Yearly.

Output source

Target extract where the results values are stored. The output source must already exist before the transform is run. The dimension mapping must be similar to that of the Input Source, i.e., containing Measure, Time, and Version dimensions.

Note: do not use the input source as an output source, as the input data may be replaced if the transform is followed by a cube load.  See the sample input and output source data preview for examples.

Output values

The name of the values column where your prediction values will be populated.

Advanced Settings

Parameters are preset by selecting Function parameter in the Main Settings.

Function Parameter



Sets the number of time units (as set in Period parameter) to predict, i.e. 5 years, 12 months, 180 days, etc. It is preset for monthly input; you can change this in the Period parameter in Main Settings.

Alogorithm Type

The AI Transform includes 12 algorithms for data analysis:

1 – Linear Model
2 – Holt Winter
3 – Seasonal Naïve
4 – Exponential Smoothing
6 – Random Walk with Drift
7 – Seasonal and Trend Decomposition using Loess (STL) model
8 – generalized STL model
9 – Neural Network Time Series Forecast
10 – TBATs model
11 – Croston’s Method
12 – Extrapolation (note that extrapolation is not AI or Machine Learning)

If “all” or “0” is entered, then all algorithms will run and the most accurate will be chosen for result.

Enter 1-12 to select a particular algorithm. Multiple algorithms can be entered with comma separation, e.g. “1,3,5”. The most accurate of the selected algorithms will be chosen for the result.

Output type

0 – output consists of rows that correspond to NumberOfPredictions selected, e.g. 12 months results in output extract with 12 rows of prediction values

1 – output consists of columns for each of the algorithms selected, e.g. 12 algorithms result in output extract with 12 columns of training accuracy values

2 – NumberOfPredictions as in output type 0, plus 2 more sets of rows with lower bounds and upper bounds. For example, if NumberOfPredictions is set for 3 months, then the resulting extract will consist of 3 rows of prediction output, plus 3 rows of lower bounds and 3 rows of upper bounds.

3 – Everything from above: NumberOfPredictions rows, lower bounds, upper bounds, as well as extra columns for each of the algorithms selected (12 algorithms = 12 columns). In the final project output, these columns could be separated/removed with a field transform.

Accuracy threshold

Minimum percentage of training accuracy required from the algorithms in order to return values, e.g. 40 = 40% accuracy must be met or no values will be returned


true – zero or null values in the source data will be replaced with meaningful values before predictions are calculated

false – zero or null values will be included in the source data sent to the algorithms


Percentage of zero/null data that will be tolerated. When the threshold is reached, an error message appears (“one or more time series has more than x% zeros”).


Source format for dates within the time series. 


Sample input source

Sample output source

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