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Course Outline

Introduction to Alteryx and the Designer Environment

  • Overview of the Alteryx Designer interface and workflow canvas
  • Configuring workflows, tool palettes, and workflow properties
  • Best practices for saving, documenting, and sharing workflows

Essential Data Preparation Tools

  • Input Data and Output Data tools: connecting to CSV, Excel, and databases
  • Select, Filter, Sort, and Browse tools for quick data inspection and pruning
  • Practical exercises: cleansing a sample dataset

Basic Data Transformation

  • Formula tool for creating calculated fields and implementing conditional logic
  • Data Cleansing: handling nulls, trimming, and standardizing values
  • Text to Columns and parsing delimited fields

Simple Data Combination

  • Join and Union techniques for combining datasets
  • Summarize for aggregation and roll-ups
  • Hands-on: building an end-to-end ETL workflow

Advanced Data Blending and Parsing (Intermediate)

  • Effectively blending multiple data sources and file formats
  • Parsing semi-structured data: understanding XML and JSON basics
  • Techniques for validating and normalizing blended data

Basic Analytical Tools and Reporting

  • Find Replace, Cross Tab, and Transpose tools for reshaping data
  • Creating simple reports and exporting results
  • Case study: generating a summarized operational report

Introduction to Macros and Reusability

  • Types of macros: Standard Macros and their use cases
  • Creating, testing, and packaging a reusable macro
  • Deploying macros within workflows to simplify processes

Workflow Automation Best Practices

  • Organizing workflows using containers and annotations
  • Considerations for error handling, logging, and scheduling
  • Practical exercise: automating a recurring data preparation task

Summary and Next Steps

Requirements

  • A foundational understanding of basic data concepts and spreadsheet applications
  • Familiarity with CSV and Excel file formats
  • Basic analytical thinking and problem-solving capabilities

Target Audience

  • Data analysts and business analysts
  • ETL practitioners and operations staff
  • Personnel responsible for automating routine data tasks
 14 Hours

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