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Duration 14 hours
Course Outline
Introduction to Alteryx and the Designer Interface
- 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
Core Data Preparation Tools
- Input Data and Output Data tools: connecting to CSV, Excel, and databases
- Select, Filter, Sort, and Browse functions for rapid data inspection and refinement
- Practical exercises: cleaning a sample dataset
Fundamental Data Transformation
- Formula tool for creating calculated fields and applying conditional logic
- Data Cleansing: managing null values, trimming, and standardizing entries
- Text to Columns for parsing delimited fields
Basic Data Integration
- Join and Union tools for merging datasets
- Summarize tool for aggregation and roll-up operations
- Hands-on exercise: constructing an end-to-end ETL workflow
Advanced Data Blending and Parsing (Intermediate)
- Effective blending of multiple data sources and file formats
- Basics of parsing semi-structured data: XML and JSON
- Methods for validating and normalizing blended data
Basic Analytical Tools and Reporting
- Find Replace, Cross Tab, and Transpose tools for data reshaping
- Generating simple reports and exporting results
- Case study: producing a summarized operational report
Introduction to Macros and Reusability
- Types of macros: Standard Macros and their appropriate use cases
- Creating, testing, and packaging reusable macros
- Integrating macros into workflows to streamline 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 solid grasp of fundamental data concepts and spreadsheet usage
- Experience with CSV and Excel file formats
- Foundational analytical thinking and problem-solving abilities
Target Audience
- Data analysts and business analysts
- ETL practitioners and operations team members
- Individuals tasked with automating routine data operations