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| Section | Objectives |
|---|---|
| Topic 1: Industry Applications | - Predictive analytics use cases
|
| Topic 2: IBM SPSS Predictive Analytics Portfolio Overview | - SPSS product positioning and value proposition
|
| Topic 3: Competitive and Solution Differentiation | - Competitive landscape understanding
|
| Topic 4: Sales Enablement and Positioning | - Customer engagement scenarios
|
1. What is the main purpose of SPSS Data Collection?
A) To integrate analytic results into business processes.
B) To retrieve existing data stored from disparate sources.
C) To gather feedback from constituents for use in advanced and predictive analytics.
D) To prepare messy data for more accurate modeling.
2. Which type of model in SPSS Modeler is BEST suited for making categorical predictions of future outcomes?
A) Anomaly detection
B) Classification
C) Association
D) Segmentation
3. A customer wants to optimize their data for simpler, more accurate, and faster models. Which family of algorithms/techniques best meets their needs?
A) Classification
B) Reduction
C) Association
D) Segmentation
4. What is NOT a key competitive differentiator of SPSS Modeler based on product feature/functionality?
A) Automated modeling and data preparation.
B) Intuitive visual interface.
C) Open and scalable architecture.
D) Scorecards and dashboards.
5. Which question is most appropriate to ask when selling SPSS Data Collection?
A) Do you have projects where knowing what your customers thought would impact your decisions?
B) How do you currently deploy your analytics results?
C) Are you able to analyze individual transactions to identify purchase patterns?
D) How consistent is your decision making?
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: B | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: A |
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