Apply Data Analytics Using SPSS Modeler Workflows
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Apply Data Analytics Using SPSS Modeler Workflows
This course is part of Apply Advanced SPSS Data Analytics & Modeling Specialization
Instructor: EDUCBA
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What you'll learn
Design end-to-end analytical workflows in SPSS Modeler using stream-based, visual analytics.
Prepare, transform, and model data using statistical and machine learning techniques.
Interpret, validate, and communicate analytical results to support real-world business decisions.
Skills you'll gain
Tools you'll learn
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February 2026
28 assignments
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There are 7 modules in this course
Learners will be able to design end-to-end analytical workflows, prepare and transform data, apply statistical and machine learning models, interpret results, and communicate actionable insights using SPSS Modeler. By the end of this course, learners will confidently build, execute, validate, and optimize analytical streams aligned with real-world business problems.
This course provides a structured, hands-on pathway to mastering SPSS Modeler, starting from foundational concepts such as workflows, node palettes, and security practices, and progressing to advanced topics including segmentation, neural networks, stream architecture, and output validation. Learners gain practical experience working with domain-specific datasets, interpreting statistical outputs, and exporting results for reporting and decision-making. What makes this course unique is its strong emphasis on visual, stream-based analytics, real-world use cases, and complete lifecycle coverageβfrom data ingestion to final insight delivery. The course balances conceptual clarity with practical execution, enabling learners to not only understand how models work, but also when and why to apply them. This course is ideal for aspiring data analysts, business analysts, and professionals seeking to apply structured, scalable analytics using SPSS Modeler in real-world scenarios.
This module introduces learners to SPSS Modeler, its analytical significance, visual workflow design, security fundamentals, and core modeling node concepts required to build structured data science streams.
What's included
8 videos4 assignments
8 videosβ’Total 61 minutes
- Introduction Significance and User Training Overviewβ’9 minutes
- Introduction Significance and User Training Workflowβ’5 minutes
- Encode Password Tool Conceptsβ’8 minutes
- Encode Password Tool Implementationβ’8 minutes
- Modeling Nodes Fundamentalsβ’11 minutes
- Node Statistics Analysisβ’6 minutes
- Node Palettes Overviewβ’8 minutes
- Node Palettes Usageβ’5 minutes
4 assignmentsβ’Total 60 minutes
- Graded-Getting Started with SPSS Modeler Foundationsβ’30 minutes
- SPSS Modeler Overview and Workflowβ’10 minutes
- Security and Modeling Basicsβ’10 minutes
- Core Modeling and Node Fundamentalsβ’10 minutes
This module focuses on understanding domain-specific datasets, performing data preparation, and interpreting statistical summaries to establish a strong analytical foundation before modeling.
What's included
8 videos4 assignments
8 videosβ’Total 66 minutes
- Banking Data Overviewβ’7 minutes
- Banking Data Processingβ’7 minutes
- High Price Analysis Overviewβ’6 minutes
- High Price Analysis Insightsβ’8 minutes
- Source Nodes and Data Importβ’10 minutes
- Graph Boards Explanationβ’12 minutes
- Statistical File Overviewβ’9 minutes
- Statistical File Interpretationβ’7 minutes
4 assignmentsβ’Total 60 minutes
- Graded-Data Understanding and Statistical Explorationβ’30 minutes
- Banking Data Introduction and Preparationβ’10 minutes
- High Price Analysis Techniquesβ’10 minutes
- Data Sources and Statistical Filesβ’10 minutes
This module develops skills in interpreting analytical outputs, applying segmentation techniques, and exporting model results for downstream consumption and decision-making.
What's included
8 videos4 assignments
8 videosβ’Total 74 minutes
- Quarterly Output Analysisβ’12 minutes
- Association and Segmentation Modeling Nodesβ’11 minutes
- Export Functionality Overviewβ’12 minutes
- Mean Output Types Overviewβ’7 minutes
- Mean Output Types Examplesβ’8 minutes
- Pistachio Data Excel Export Nodeβ’10 minutes
- Hierarchical Density Based Scan Modelβ’9 minutes
- Streams Architecture Overviewβ’6 minutes
4 assignmentsβ’Total 60 minutes
- Graded-Output Analysis and Segmentation Modelingβ’30 minutes
- Output and Segmentation Foundationsβ’10 minutes
- Exporting and Mean Output Interpretationβ’10 minutes
- Advanced Modeling and Data Exportβ’10 minutes
This module covers the architectural design of SPSS Modeler streams, execution flow management, recovery mechanisms, and advanced data operations for reliable analytics.
What's included
9 videos4 assignments
9 videosβ’Total 71 minutes
- Streams Execution Flowβ’8 minutes
- Auto Recovery Featuresβ’10 minutes
- Stream Description Fundamentalsβ’8 minutes
- Running Streams Practicallyβ’9 minutes
- Working with Data Basicsβ’5 minutes
- Working with Data Transformationsβ’10 minutes
- Working with Data Advanced Operationsβ’5 minutes
- Housing Price Index Analysis Overviewβ’6 minutes
- Housing Price Index Data Modelingβ’9 minutes
4 assignmentsβ’Total 60 minutes
- Graded-Stream Architecture and Executionβ’30 minutes
- Stream Structure and Recoveryβ’10 minutes
- Practical Stream Executionβ’10 minutes
- Advanced Data Operations and Modelingβ’10 minutes
This module emphasizes result interpretation, dashboard visualization, execution scenario analysis, and default configuration best practices to support insight communication.
What's included
8 videos4 assignments
8 videosβ’Total 70 minutes
- Housing Price Index Result Interpretationβ’3 minutes
- Dashboard Chart Designβ’10 minutes
- Output Management and Visualizationβ’11 minutes
- Executing the Current Streamβ’12 minutes
- Location Price Date Analysisβ’13 minutes
- Default Settings Configurationβ’7 minutes
- Default Settings Best Practicesβ’7 minutes
- Modeling Nodes Overviewβ’8 minutes
4 assignmentsβ’Total 60 minutes
- Graded-Visualization, Dashboards, and Configurationβ’30 minutes
- Interpreting Analytical Resultsβ’10 minutes
- Stream Execution and Analysis Scenariosβ’10 minutes
- Untitledβ’10 minutes
This module explores advanced statistical modeling, neural network concepts, execution dependencies, and reporting techniques for complex analytical solutions.
What's included
8 videos4 assignments
8 videosβ’Total 63 minutes
- Modeling Nodes Use Casesβ’7 minutes
- Advanced Statistical Model Outputβ’7 minutes
- Advanced Statistical Model Interpretationβ’9 minutes
- Neural Network Conceptsβ’6 minutes
- Neural Network Applicationsβ’9 minutes
- Status Analysis Reportβ’8 minutes
- Streams and Nodes Relationshipsβ’9 minutes
- Streams and Nodes Execution Flowβ’8 minutes
4 assignmentsβ’Total 60 minutes
- Graded-Advanced Modeling and Neural Networksβ’30 minutes
- Advanced Modeling Outputsβ’10 minutes
- Neural Network Fundamentalsβ’10 minutes
- Stream Relationships and Reportingβ’10 minutes
This capstone module integrates stream design, execution, validation, and result communication to deliver complete, decision-ready analytical solutions.
What's included
10 videos4 assignments
10 videosβ’Total 70 minutes
- Bank Indicator and Sort Node Overviewβ’8 minutes
- Bank Indicator and Sort Node Implementationβ’7 minutes
- Process Nodes Overviewβ’9 minutes
- Building a Stream Fundamentalsβ’5 minutes
- Building a Stream Hands Onβ’8 minutes
- Advanced Stream Designβ’5 minutes
- Advanced Stream Executionβ’9 minutes
- Output Running Basicsβ’7 minutes
- Output Running Validationβ’5 minutes
- Output Running Final Resultsβ’6 minutes
4 assignmentsβ’Total 60 minutes
- Graded-End-to-End Stream Design and Final Outputsβ’30 minutes
- Banking Indicators and Process Nodesβ’10 minutes
- Stream Building and Advanced Designβ’10 minutes
- Execution, Validation, and Final Resultsβ’10 minutes
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