Alteryx Day 18 – Data Blending Explained

Welcome to Day 18 of the 100 Days of Alteryx Learning Series!
In this lesson, we cover Data Blending, a key concept for combining data from multiple sources to create a unified, analysis-ready dataset.

Data blending is essential when working with different file formats, systems, or data structures.

What You Will Learn Today
🔗 What is Data Blending?

• Difference between data blending and data joining
• When to blend data instead of merging
• Common data blending scenarios

🧩 Tools Used in Data Blending

• Join Tool
• Union Tool
• Append Fields Tool
• Formula Tool for alignment
• Select Tool for schema standardization

🛠 Key Concepts

• Matching keys and grain
• Handling different data types
• Managing unmatched records
• Resolving schema mismatches
• Data validation after blending

Real-World Use Cases

• Blending CRM data with transaction data
• Combining Excel files with database tables
• Enriching datasets with lookup values
• Blending API data with internal systems
• Preparing blended data for analytics and reporting

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

• Understand how data blending works
• Choose the right tools for blending scenarios
• Handle schema and key mismatches
• Build clean and reliable blended datasets

Perfect For

Beginners, data analysts, BI developers, and data engineers working with multi-source data.

#alteryx #alteryxexamples #alteryxtutorial #dataanlysis #dataanalytics #datavisualization #datascience #database #machinelearning #pythonprogramming #python #pythontutorial #coding #codinglife #codingtips #codingtutorial #youtubeshorts #youtubevideo #youtubeshort #youtubechannel