Post by account_disabled on Dec 6, 2023 21:24:19 GMT -6
Machine Learning at SAC The tool for building a report in SAC based on an existing data model gives us the opportunity to use Machine Learning mechanisms. Machine learning enables us to discover patterns and relationships that are statistically significant to our data source. When running such an analysis for a previously used sales model the user only needs to indicate which element of the model will be the subject of the study whether it will be a dimension or measure and then indicate which other elements are to be assessed in terms of their impact on the analyzed variable that is part of the model. For example by indicating the gross margin measure as the main object of our analysis we can obtain.
The following result Summary overview a summary showing the trend of values in past periods along with forecast values for future months calculated on the basis of historical data distribution of values for a given measure showing the most typical values for our measure analysis of Email Marketing List aggregates using the dimensions available in the model SAP Business Intelligence Key influencers Indication of model objects that statistically have the greatest impact on the examined variable. In the analyzed model the Product dimension was indicated as the factor having the greatest impact on the analyzed variable. In other words the margin on selected products varies greatly.
Unexpected values Identification of transactions in which the value of the tested variable differs significantly from the value predicted using the built model. These types of values may be the subject of further analysis to clarify or verify the correctness of completed transactions. Simulation Simple mechanisms for whatif analysis. It allows you to assess the impact of changing individual model parameters on the examined variable such as a change in the discount value for selected products.
The following result Summary overview a summary showing the trend of values in past periods along with forecast values for future months calculated on the basis of historical data distribution of values for a given measure showing the most typical values for our measure analysis of Email Marketing List aggregates using the dimensions available in the model SAP Business Intelligence Key influencers Indication of model objects that statistically have the greatest impact on the examined variable. In the analyzed model the Product dimension was indicated as the factor having the greatest impact on the analyzed variable. In other words the margin on selected products varies greatly.
Unexpected values Identification of transactions in which the value of the tested variable differs significantly from the value predicted using the built model. These types of values may be the subject of further analysis to clarify or verify the correctness of completed transactions. Simulation Simple mechanisms for whatif analysis. It allows you to assess the impact of changing individual model parameters on the examined variable such as a change in the discount value for selected products.