How This Workflow Works
This workflow demonstrates two approaches to merging tables: a straightforward value-based lookup and a more flexible join operation. It shows how to enrich one dataset with information from another, using both simple and advanced merging operations.
Key Features:
- Combine related data from two tables using shared keys
- Enrich one dataset with additional attributes from another
- Choose between simple lookups and more complex join conditions
- Adapt merging strategy to fit the complexity of your data relationships
Step-by-step:
1. Access Source Data:
The process starts by accessing two separate datasets—one for stores and another for products. Each dataset is structured to include relevant attributes, such as store locations and product categories, ensuring both are ready for merging.
2. Merge Datasets with Value Lookup:
A value-based lookup is used to add information from one table to another. This method quickly matches and appends data based on a single key, making it suitable for straightforward merging tasks where the relationship between tables is direct.
3. Merge Datasets with a Join Operation:
For more complex scenarios, a join operation is performed. This step combines the two datasets using specified join conditions, allowing for flexible merging based on multiple keys or more advanced matching logic (e.g., right join, left join, full join). This approach supports inner joins to ensure only matching records are included.
4. Compare Merged Results:
Lastly, the workflow allows you to review the outcomes of both merging strategies side by side. This comparison helps you understand the differences between simple lookups and advanced joins, and choose the method that best fits your data merging needs.