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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

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

Simple Data Combination

  • Join and Union tools for combining datasets.
  • Summarize tool for aggregation and roll-ups.
  • Hands-on activity: 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

  • Understanding 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 with containers and annotations.
  • Error handling, logging, and scheduling considerations.
  • Practical exercise: automating a recurring data preparation task.

Summary and Next Steps

Requirements

  • Familiarity with basic data concepts and spreadsheet applications.
  • Understanding of CSV and Excel file formats.
  • Foundational analytical thinking and problem-solving abilities.

Audience

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

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