What's New in Data Mining Deployment Guide, Version 7.7.1 Rev A
Table 1 lists topics in this version of the documentation to support Release 7.7.1 of the software.
Table 1. New Product Features in Data Mining Deployment Guide, Version 7.7.1 Rev A
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About Siebel Data Mining Workbench |
Connecting to analytics data sources requires installation of an instance of the analytics ODBC driver on the Siebel Data Mining Workbench client. |
About Siebel Miner |
Connecting to analytics data sources requires installation of an instance of the analytics ODBC driver on the Siebel Miner server. |
Process of Configuring Siebel Analytics for Real-Time Deployment |
Added content on column data types for the Probability and Score columns provided by predictive models. |
Example of Using the Data Mining Subject Area |
Using analytics metadata that joins batch score records to Account, Contact, or Product entities requires that the ID column of the batch score records matches the ROW_WID of these entities. |
What's New in Data Mining Deployment Guide, Version 7.7.1
Table 2 lists topics in this version of the documentation to support Release 7.7.1 of the software.
Table 2. New Product Features in Data Mining Deployment Guide, Version 7.7.1
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Overview of Siebel Data Mining Installation |
This chapter gives an overview of general installation requirements for the Siebel Data Mining products. |
Setting Up a Modeling Environment with Siebel Data Mining |
This chapter shows how to set up a Siebel Data Mining modeling environment with Siebel Analytics as the underlying data source. |
Deploying Real-Time Scoring with Siebel Data Mining |
This chapter explains how to configure Siebel Analytics and Siebel operational applications for deploying predictive models in real-time scoring scenarios. Real-time scoring is the process of scoring a single customer (or other entities like Account and Household) on demand in an operational application (such as Siebel Call Center). |
Setting Up Batch Scoring with Siebel Data Mining |
This chapter explains how to configure and use Siebel Answers for deploying predictive models in batch scoring scenarios. Batch scoring is the process of scoring a group of customers (or other entities like Account and Household) in a single batch run, and using those scores for further analysis with Siebel Analytics and driving segmentation with Siebel Marketing. |
NOTE: Chapters 4 through 6 use the example of a wireless service provider managing customer churn with the help of predictive analytics. Using predictive analytics to pursue business objectives other than churn management follows a very similar setup and configuration process.
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