Choose
Next
to continue.
Enter Select Project ID prompt values to filter the data set i.e. 3019767
After entering the value, choose
OK
to begin modeling
Choose
Analyze
and a description for the data set appears.
Choose
Next
when the data description accurately describes the data
The data set description was previously completed during the data manipulation steps. You will
not need to change anything in this window
Choose Next to Selecting Variables screen
In the Selecting Variables screen,
a. Time: select PERIODSTARTDATE
b. Target: select TURNOVER. Re-run using PROJECT_EBIT
c. Exclude Variable: Select PROJECT_ID, CUSTOMERID.
d. Last Training Date: select Date and change to last valid transaction date.
Select Next. Review Summary of Modeling Parameter to set additional setting.
Enter Number of Forecasts: 12
Select Generate. Engine runs the Training the Model. Review the Model Overview.
In the Using the Model screen, select Display and review the resulting model by viewing Model
Overview, View Forecasts, Regressions: Contributions by Variables, and so on.
After reviewing the model results, choose Save/Export and select Apply Model
In the Applying the Model screen
Application Data Set
Data Type
: Data Base
Folder
: HANA ODBC connection
Data:
DM_TS_PROJECT_TOTAL - enter Select Project ID
Generation Options
Generate:
Predicted Value Only
Results Generated by the Model
Data Type:
Text Files
Folder:
local folder
Data
: result_ts_forecast_selected_project_turnover.txt
Select
Apply
After reviewing model results, choose
Next
.
Choose
Save Model
Saving the Model
Model Name:
default
Description:
description of model
Data Type:
Text Files
Folder:
local folder
File/Table:
md_timeseries_selected_project_turnover.txt
Choose
Save
To repeat the process for another variable PROJECT_EBIT, choose
Previous
to go back.
Continue to choose
Previous
, to return to
Selecting Variables
screen.
Select
Target: PROJECT_EBIT
and repeat steps 12 to 21. Change the model name and result file
name appropriately.
