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Duration 14 hours
Course Outline
Introduction to Power Query
- Overview of the Power Query interface
- Grasping the concept of queries and applied steps
- Navigating the integration with Power BI and Excel
Connecting to Data Sources
- Ingesting data from Excel, CSV, and text files
- Managing folders and structured datasets
- Establishing connections to online and database sources
Data Cleaning Fundamentals
- Eliminating errors and duplicate entries
- Filtering, sorting, and reshaping data structures
- Handling missing values effectively
Transformations and Data Shaping
- Splitting and merging columns
- Applying pivoting and unpivoting techniques
- Grouping and aggregating data for analysis
Combining Queries
- Differentiating between appending and merging queries
- Understanding join types and data structure implications
- Modelling datasets from multiple sources
Introduction to M Language
- Comprehending M formulas
- Modifying queries via the Advanced Editor
- Developing custom transformation logic
Automation and Refresh
- Designing reusable transformation workflows
- Setting up automated refresh schedules
- Optimising dependencies and query performance
Advanced Techniques
- Implementing parameterised queries
- Utilising functions within M
- Adopting best practices for scalable transformation pipelines
Summary and Next Steps
Requirements
- A solid grasp of spreadsheet-based data management
- Hands-on experience with fundamental data analysis tasks
- Familiarity with standard file formats, including CSV and Excel
Target Audience
- Data specialists responsible for cleaning and preparing datasets
- Business analysts managing recurring data workflows
- Professionals 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
