Data Analytics Workflows with SPSS Modeler

To make confident business decisions, you need to know how to clean, structure, and analyze your data efficiently. SPSS Modeler provides a powerful visual workflow environment that simplifies complex data science tasks without requiring extensive coding. This text-based course guides you through the fundamentals of data analytics using SPSS Modeler workflows. You will start with core data concepts, progress to data preparation and transformation techniques, and learn how to build and evaluate predictive models to solve real-world problems. What you'll learn: - Understand foundational data analytics terminology and the SPSS Modeler interface. - Import and merge data from various sources into a unified workflow. - Clean and transform raw data using filtering, field operations, and type definitions. - Apply statistical and predictive modeling techniques to uncover hidden patterns. - Analyze workflow outputs to generate actionable business reports. - Implement modern data preparation best practices to ensure data quality and consistency. You will begin by learning key terminology and navigating the interface before moving on to practical step-by-step workflow construction. The material guides you through data ingestion, cleaning, modeling, and exporting results in structured text-based lessons. This course is designed for beginners, aspiring data analysts, and business professionals looking to understand workflow-based data preparation. No prior programming or statistical modeling experience is required. Start building your first analytical workflow today and turn raw data into valuable insights.