Alteryx Day 25 – RegEx Scenarios Explained

Описание: Welcome to Day 25 of the 100 Days of Alteryx Learning Series!
Today’s lesson focuses on real-world RegEx scenarios, where we apply RegEx patterns to solve common data cleaning and transformation problems in Alteryx.

This session helps bridge the gap between understanding RegEx syntax and using it effectively in practical workflows.

What You Will Learn Today
🔍 Common RegEx Scenarios

• Extracting numeric values from text
• Validating email and phone number formats
• Cleaning special characters
• Standardizing codes and IDs
• Parsing mixed alphanumeric strings

🛠 RegEx Tool Applications

• Using Parse to extract values
• Using Replace to clean text
• Using Match for validation
• Working with capturing groups
• Handling multiple matches

🧩 Combining RegEx with Other Tools

• RegEx with Formula Tool
• RegEx with Data Cleansing
• RegEx with Text to Columns
• Validating outputs with Browse

Real-World Use Cases

• Cleaning CRM and customer datasets
• Parsing log and system-generated data
• Standardizing product and transaction codes
• Validating input data quality
• Preparing text data for analytics

By the End of This Video, You Will Be Able To:

• Apply RegEx confidently in real scenarios
• Choose the right RegEx method
• Build reusable RegEx logic
• Improve data quality and consistency

Perfect For

Data analysts, BI developers, data engineers, and anyone handling complex text data in Alteryx.


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