IBM C2090-930 Exam Dumps

Last Updated: May 17th, 2024

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IBM C2090-930 Exam Dumps

Number of questions: 60
Number of questions to pass: 40
Time allowed: 90 minutes



The candidate has understanding of analytical solutions, is aware IBM SPSS Modeler capabilities, has understanding of the IBM SPSS Modeler facts version, can practice regular methodologies to each engagement and increase SPSS predictive fashions.

To obtain the IBM Certified Specialist – SPSS Modeler Professional certification, applicants ought to own the talents recognized below Recommended Prerequisite Skills, if any, and byskip one (1) exam.

Upon final touch of this technical certification the a hit candidate indicates having the essential understanding to take part as an powerful group member withinside the implementation of IBM SPSS Modeler Professional analytics solution.

Recommended Skills

The following are subjects which are assumed earlier than your check education and could now no longer be examined on :

Database and ODBC concepts

Basic talent in statistical concepts

Knowledge of primary laptop programming


Exam C2090-930: IBM SPSS Modeler Professional v3

Exam Objectives

Number of questions: 60

Number of inquiries to byskip: 40

Time allowed: 90 minutes

Status: Live


Section 1: Business Understanding and Planning10�scribe the CRISP-DM process

Describe a way to map commercial enterprise goals to facts mining goals


Section 2: Data Preparation20�scribe strategies for facts transformation (for example, Derive node, Auto Data Prep node, Data Audit node and Filler node)

Describe a way to combine facts (for example, Merge node and Append node)

Describe sampling, partitioning, and balancing facts (for example, Sample node, Balance node and Partition node)

Describe strategies for refining facts (for example, Select node, Filter node and Aggregate node)


Section 3: Data Understanding15�scribe suitable nodes for precis statistics, distributions, and visualizations (for example, graph nodes, output nodes)

Describe facts pleasant issues (for example, outliers and lacking facts)


Section 4: Deployment10�scribe a way to use Export nodes (equipment for exporting facts)

Identify a way to rating new facts the usage of fashions

Identify SPSS Modeler reporting strategies


Section 5: Evaluation and Analysis15�monstrate a way to interpret SPSS Modeler results (for example, the usage of Evaluation node, Analysis node, and facts visualizations)

Describe a way to use version nugget interfaces


Section 6: Modeling20�scribe category fashions (consisting of GLM and regression)

Describe segmentation fashions

Describe affiliation fashions

Describe vehiclemobile modeling nodes

Demonstrate a way to integrate fashions the usage of the Ensemble node


Section 7: SPSS Modeler Professional Functionality10%

Identify the motive of every palette

Describe using SuperNodes

Describe the blessings of SPSS Modeler scripting



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