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 Duration 14 hours

Course Outline

Introduction to Alteryx and the Designer Environment

  • Overview of the Alteryx Designer interface and workflow canvas
  • Configuration of 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 database sources
  • Using Select, Filter, Sort, and Browse for rapid data inspection and pruning
  • Practical exercises: cleansing a sample dataset

Basic Data Transformation

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

Simple Data Combination

  • Join and Union tools for merging datasets
  • Summarize for performing aggregation and roll-ups
  • Hands-on activity: constructing an end-to-end ETL workflow

Advanced Data Blending and Parsing (Intermediate)

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

Basic Analytical Tools and Reporting

  • Find Replace, Cross Tab, and Transpose for reshaping data structures
  • Generating simple reports and exporting results
  • Case study: producing a summarized operational report

Introduction to Macros and Reusability

  • Types of macros: Standard Macros and appropriate 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 fundamental understanding of basic data concepts and spreadsheets
  • Experience with CSV and Excel file formats
  • Basic analytical thinking and problem-solving capabilities

Target Audience

  • Data analysts and business analysts
  • ETL practitioners and operations team members
  • Individuals responsible for automating routine data tasks

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