Alteryx: Basic & Intermediate - Practical Data Preparation and Automation Training Course

Introduction to Alteryx Designer Environment

• Survey of the Alteryx Designer interface and workflow canvas
• Configuration of workflows, tool palettes, and system properties
• Guidelines for preserving, documenting, and distributing workflows for government operations

Core Data Preparation Utilities

• Input and Output tools for connectivity with CSV, Excel, and database systems
• Utilization of Select, Filter, Sort, and Browse utilities for data inspection and filtering
• Applied exercises involving the cleansing of sample datasets

Fundamental Data Transformation Techniques

• Employment of Formula tools for calculated fields and conditional logic
• Data cleanup procedures: management of null values, trimming, and standardization
• Parsing of delimited fields using Text to Columns

Fundamentals of Data Combination

• Application of Join and Union tools for dataset integration
• Use of Summarize tool for data aggregation and roll-ups
• Practical application: construction of an end-to-end ETL workflow

Advanced Data Blending and Parsing (Intermediate Level)

• Effective integration of diverse data sources and file formats
• Parsing semi-structured data including XML and JSON fundamentals
• Methods for validation and normalization of blended datasets

Core Analytical Tools and Reporting Capabilities

• Data reshaping using Find Replace, Cross Tab, and Transpose tools
• Generation of basic reports and export of results
• Case study: production of a summarized operational report

Introduction to Macros and Reusability

• Classification of macros, including Standard Macros and their appropriate use cases
• Development, testing, and packaging of reusable macro components
• Deployment of macros within workflows to streamline processes for government agencies

Workflow Automation Standards

• Organization of workflows via containers and annotations
• Strategies for error handling, logging, and scheduling
• Practical exercise: automation of recurring data preparation tasks

Summary and Future Directions