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Duration 14 hours
Course Outline
Getting Started with Power Query
- Overview of the Power Query interface
- Grasping the concept of queries and applied steps
- Exploring integrations with Power BI and Excel
Establishing Data Connections
- Ingesting Excel, CSV, and text files
- Handling folders and structured datasets
- Linking to online services and database sources
Essentials of Data Cleaning
- Eliminating errors and duplicate entries
- Applying filters, sorting, and data shaping techniques
- Addressing missing values effectively
Data Transformation and Shaping
- Splitting and merging column data
- Utilizing pivot and unpivot operations
- Grouping and aggregating data sets
Integrating Multiple Queries
- Distinguishing between appending and merging queries
- Considerations for join types and data structure
- Modeling datasets derived from multiple sources
Overview of the M Language
- Comprehending M formulas
- Modifying queries via the Advanced Editor
- Developing custom transformation logic
Automation and Refresh Mechanisms
- Building reusable transformation workflows
- Setting up refresh schedules
- Overseeing dependencies and query performance
Advanced Strategies
- Implementing query parameters
- Applying functions within M
- Best practices for scalable transformation pipelines
Recap and Future Directions
Requirements
- A foundational grasp of spreadsheet-based data operations
- Experience performing basic data analysis tasks
- Familiarity with standard file formats, including CSV and Excel
Target Audience
- Data professionals tasked with 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