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FormateurAlaa Hady MBA, AI Engineer
Associé gérant, Advanced Management Solutions
Instructor: Alaa Hady · Language: English or Arabic · Suggested duration: 1 day · Level: Beginner to Intermediate (Level 200)
Objectives
- Standardize messy, inconsistent business data into analysis-ready tables.
- Build repeatable, self-documenting data transformation pipelines.
- Combine data dynamically from multiple folders, sheets, and disparate sources.
- Maximize refresh speed using Query Folding and troubleshoot common M errors.
Outline and contents
- Power Query Editor architecture, M language fundamentals, and managing Applied Steps
- Handling data types, regional locales, nulls, errors, and duplicate keys
- Text, number, and date transformations: splitting, extracting, conditional columns, and Column from Examples
- Combining queries: Merge (join types and fuzzy matching) versus Append
- Automating folder ingestion and handling schema drift across monthly files
- Reshaping data: Pivoting, Unpivoting, Grouping, and transposing complex spreadsheet headers
- Parameters, custom functions, and staging queries for modular architecture
- Query Folding mechanics, viewing native queries, and performance-aware data preparation
- Data quality profiling (column quality, distribution, profile) and refresh troubleshooting
- Intensive hands-on data-wrangling lab
Target audience
Power BI developers, Excel power users, data analysts, finance analysts, and reporting teams.
Expected outcomes
Participants can automate complex data cleaning routines, ingest multi-file structures reliably, preserve query folding for fast refreshes, and resolve broken transformation pipelines.
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