Introduction to Aster Scoring SDK - Aster Analytics

Teradata AsterĀ® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
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uce1497542673292.ditamap
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dita:id
B700-1022
lifecycle
previous
Product Category
Software

Aster Scoring SDK is intended for systems that follow events in real time and must take action based on these events in real time with the support of analytics. Aster Scoring SDK applies predictive analytics to make timely decisions based on real events. Aster Scoring SDK also makes Aster Analytics functions available for real-time prediction.

Use cases for Aster Scoring SDK include:
  • Fraud prevention
  • Churn reduction
  • System failure predictions
  • Site personalization
  • Purchase recommendations
  • Dynamic promotion pricing

The workflow of Aster Scoring SDK is a four-step process:



  1. Model training/data loading

    Train a model in the same way on Aster framework. Load any additional tables (such as dictionary or rules for text analytics) on the database or install them as files on database.

  2. AML generation

    Run the AMLGenerator function on the model (from Step 1) and relevant information for the corresponding function.

  3. AML file transfer

    Download the .aml file from Aster framework (if using an ACT terminal, use the command \download amlfile). Export (upload) it to the system, working in real time and using any standard ssh/scp client tool.

  4. Scorer execution

    Use the Scorer API to score input requests (queries), based on the trained model in the .aml file.