Video 3 Carga Productos
Loading Product Information and Data Transformation
Introduction to Data Loading
- The previous video covered loading an input category file with four categories and discussed the necessary configuration changes for data sources.
- In this video, the focus shifts to loading product information from an Excel file, moving away from previous options.
Importing Data from Excel
- The process involves locating the Excel file containing product data, which is recognized by Excel as a table named "productos."
- Regardless of which table is selected, the information remains consistent across tables; variations depend on available data.
Transforming Data Steps
- The transformation process includes three main steps: origin, navigation, and header management.
- A new step involves selecting the specific sheet within the Excel workbook that contains product data.
Suggestions for Efficient Data Transformation
- It’s recommended to perform all necessary transformations first before removing any columns to avoid redundancy in steps.
- Understanding cost versus price is crucial; cost refers to production expenses while price indicates selling value.
Changing Data Types
- Product costs need conversion into a currency format; this can be done by selecting appropriate numeric types with decimals.
- Similar transformations apply to product prices, ensuring consistency in data formatting throughout.
Reviewing Additional Information
- Other attributes like product category and subcategory are confirmed as correct numeric types without further changes needed.
- A column labeled "wiki" contains numerical values representing categories; there’s potential for enhancing clarity by replacing numbers with category names.
Combining Queries for Enhanced Clarity
Merging Queries
- To improve readability, merging queries allows numerical representations of categories to be replaced with their respective names through a combination of queries.
Steps for Combining Queries:
- Select the option to combine queries.
- Choose relevant tables (categories).
Understanding Data Transformation in a Joint System
Overview of Column Configuration
- The joint system allows for similar functionality as previous configurations, recommending settings that include a left-side nerve configuration.
- A new column labeled "categories" is created, which pulls information from existing categories that match the product data from Wiki.
Information Extraction Process
- Users can expand the view to see all columns related to the selected product without needing to select Wiki products again.
- By selecting specific options, users can rename categories for clarity, eliminating unnecessary numeric identifiers and displaying only relevant category names.
Renaming and Prefixed Adjustments
- Automatic renaming occurs based on source information; however, users have the option to customize prefixes for better clarity.
- Users can delete or modify prefixes directly through settings, enhancing the organization of their data presentation.
Managing Columns and Data Integrity
- Additional transformations may involve removing unnecessary columns that do not contribute to sales modeling or analysis.
- Users are encouraged to utilize keyboard shortcuts (like Control + click) for efficient multi-column selection when deleting unneeded data.
Recovery of Deleted Information
- If a column is mistakenly deleted, users can easily revert changes by editing their queries without losing original data integrity.
- The system retains all steps executed within the current version of the file, allowing users to recover any lost information seamlessly.
Conclusion on Data Management Practices
- There’s no need for concern when deleting columns since all actions are reversible within the query context; original files remain untouched.