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Duration 14 hours
Course Outline
Introduction to Power Query
- Overview of the Power Query interface
- Grasping queries and applied steps
- Exploring integrations with Power BI and Excel
Connecting to Data Sources
- Importing data from Excel, CSV, and text files
- Handling folders and structured datasets
- Establishing connections to online and database sources
Data Cleaning Fundamentals
- Eliminating errors and duplicates
- Filtering, sorting, and restructuring data
- Addressing missing values
Transformations and Data Shaping
- Splitting and merging columns
- Performing pivots and unpivots
- Grouping and aggregating data
Combining Queries
- Distinguishing between append and merge queries
- Considering join types and data structure
- Modeling datasets from multiple sources
Introduction to M Language
- Understanding M formulas
- Modifying queries via the Advanced Editor
- Developing custom transformations
Automation and Refresh
- Building reusable transformation workflows
- Setting up refresh schedules
- Managing dependencies and query performance
Advanced Techniques
- Parameterizing queries
- Applying functions within M
- Best practices for scalable transformation pipelines
Summary and Next Steps
Requirements
- A foundational understanding of spreadsheet-based data work
- Prior experience with basic data analysis tasks
- Familiarity with standard file formats, including CSV and Excel
Target Audience
- Data professionals responsible for cleaning and preparing datasets
- Business analysts managing recurring data workflows
- Individuals involved in data reporting and process automation
Testimonials (2)
The most valuable takeaway was learning how to apply the concepts in real-world scenarios and understanding the tools and processes.
Marcel Tansae - DB Technology
Course - Microsoft Power Automate
How to use relationships in Power BIand the differences between columns and measurements