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Duration 14 hours
Course Outline
Getting Started with Alteryx and the Designer Interface
- Exploring the Alteryx Designer layout and workflow canvas
- Setting up workflows, toolbars, and configuration properties
- Recommended approaches for storing, documenting, and distributing workflows
Core Data Preparation Utilities
- Using Input Data and Output Data tools to connect to CSV, Excel, and database sources
- Employing Select, Filter, Sort, and Browse tools for rapid data review and refinement
- Practical task: cleaning a representative dataset
Foundational Data Manipulation
- Applying the Formula tool for creating computed fields and conditional statements
- Data cleansing techniques: managing null values, trimming whitespace, and standardizing entries
- Utilizing Text to Columns and parsing delimited data
Basic Dataset Integration
- Merging datasets using Join and Union tools
- Performing aggregations and roll-ups with the Summarize tool
- Hands-on project: constructing a complete ETL process
Advanced Blending and Parsing Techniques (Intermediate)
- Effectively integrating multiple data sources and file formats
- Interpreting semi-structured data: fundamentals of XML and JSON
- Strategies for verifying and normalizing combined datasets
Entry-Level Analytics and Reporting
- Reshaping data using Find Replace, Cross Tab, and Transpose
- Generating basic reports and exporting outcomes
- Scenario analysis: creating a summarized operations report
Introduction to Macros and Code Reuse
- Understanding Standard Macros and their appropriate use cases
- Developing, validating, and packaging reusable macro components
- Implementing macros within workflows to reduce process complexity
Best Practices for Workflow Automation
- Structuring workflows using containers and descriptive annotations
- Considering error management, logging, and scheduling parameters
- Practical application: automating a repetitive data preparation routine
Conclusion and Future Directions
Requirements
- Foundational knowledge of data concepts and spreadsheet usage
- Comfort with CSV and Excel file structures
- Essential analytical reasoning and troubleshooting abilities
Target Audience
- Business and Data Analysts
- ETL specialists and operations personnel
- Professionals managing the automation of routine data processes
