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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.
- 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 rapid data inspection and refinement.
- Practical exercises: cleansing a sample dataset.
Basic Data Transformation
- Formula tool for creating calculated fields and conditional logic.
- Data Cleansing: managing nulls, trimming whitespace, and standardizing values.
- Text to Columns and parsing delimited fields.
Simple Data Combination
- Join and Union tools for merging datasets.
- Summarize tool for aggregation and roll-ups.
- Hands-on session: building an end-to-end ETL workflow.
Advanced Data Blending and Parsing (Intermediate)
- Effective blending of 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 tools for reshaping data.
- 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 use cases.
- Creating, testing, and packaging a reusable macro.
- Integrating macros into 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 spreadsheets.
- 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.
- Professionals responsible for automating routine data tasks.