1. Aligning raw data with reporting templates
Challenge: Sales, marketing, and finance teams export data in different column structures, making consolidation impossible.
Magic Table Solution: Select a reporting template — for example, “Monthly Sales Summary” — and map columns from your files (e.g., “Sales Date” → “date”, “Net Value” → “revenue”).
Example: Format monthly exports from 3 marketplaces into a single Power BI-compatible template.
Benefits:
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No need for manual column renaming.
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Immediate compatibility with dashboards.
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Saves hours of spreadsheet formatting.
2. Structuring supplier or customer data
Challenge: Supplier or customer exports often use inconsistent field names.
Magic Table Solution: Choose your preferred structure and align each file to match.
Example: Map “Customer Name”, “Client”, and “Buyer” columns from different sources into a unified “Customer_Name” field.
Benefits:
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Consistent datasets across departments.
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Ready-to-analyze tables.
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Easier imports into CRMs or ERPs.
3. Preparing data for analysis tools
Challenge: Analysts waste time cleaning data before importing it into Power BI, Tableau, or Google Sheets.
Magic Table Solution: Reformat any dataset according to a BI-friendly structure — including standardized headers and consistent ordering.
Example: Transform Excel exports from different sales systems into a single, analytics-ready structure.
Benefits:
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Clean data for faster insights.
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Reusable templates for recurring reports.
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Zero risk of broken formulas or column mismatch.