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Test C2020-010: IBM SPSS Modeler Professional v2


Business Understanding (5%)


  1. CRISP-DM process methodology

  2. Identifying business objectives

  3. Translating business objectives to data mining goals


Data Understanding (25%)


  1. Read data from various sources - Source nodes

  2. Use data visualization - Graph nodes

  3. Understand distributions and summary statistics

  4. Identify data quality issues

  5. Identify and understand outliers

  6. Identify anomalies - Anomaly node

  7. Understand relationships among variables


Data Preparation (35%)


  1. Combine datasets using the Merge and Append nodes

  2. Derive new fields - Fields Pallet nodes

  3. Aggregate and restructure datasets

  4. Use the Select node

  5. Sampling and balancing datasets

  6. Methods for reducing the dimensionality of the dataset

  7. Understand SQL pushback

  8. Understand use of data caching

  9. Methods for missing value replacement


Modeling (20%)


  1. Partition the dataset

  2. Understand which models to use for sets or binary outcomes

  3. Understand which models to use for numeric outcomes

  4. Understand model types and basic operations

  5. Combine models using the Ensemble node

  6. Auto modeling nodes


Evaluation of Results (10%)


  1. Use the Analysis node

  2. Produce and interpret Evaluation charts

  3. Interpret model results using data visualizations (charts) and classification tables

  4. Interpret Generated Model Nuggets


Deployment of Results (5%)


  1. Use the Export nodes

  2. Score new data using generated models

  3. Understand monitoring of deployed models



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