In this 2-hour long project-based course, you will learn how to transform date, time, and duration data for analysis in Power BI, merge and clean datasets by handling inconsistencies and outliers, and apply mean imputation and other cleaning techniques to prepare data for predictive modeling.



PowerBI for Beginners: Data transformation

Instructor: Ahmad Varasteh
Access provided by New Apprenticeship
2,101 already enrolled
(15 reviews)
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What you'll learn
- Transform date, time, and duration data for analysis in Power BI. 
- Merge and clean datasets by handling inconsistencies and outliers. 
- Apply mean imputation and other cleaning techniques to prepare data for predictive modeling. 
Skills you'll practice
Details to know

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Only available on desktop
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Learn, practice, and apply job-ready skills in less than 2 hours
- Receive training from industry experts
- Gain hands-on experience solving real-world job tasks
- Build confidence using the latest tools and technologies

About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
- Load and Explore Flight Data in Power BI 
- Transform Dates and Extract Airplane Models 
- Convert Times and Durations for Analysis 
- Practice Task 
- Merge Flight and Route Data for Integration 
- Handling Outliers and Missing Values 
- Cumulative Activity 
Recommended experience
Understanding of basic data concepts (e.g., tables, rows, columns). Basic knowledge of Excel or any spreadsheet tool for handling data.
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How you'll learn
- Skill-based, hands-on learning - Practice new skills by completing job-related tasks. 
- Expert guidance - Follow along with pre-recorded videos from experts using a unique side-by-side interface. 
- No downloads or installation required - Access the tools and resources you need in a pre-configured cloud workspace. 
- Available only on desktop - This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices. 
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