We may earn an affiliate commission when you visit our partners.
Course image
Eugene Meidinger
In order to model your data in Power BI, you need to clean it up first. In this course, Power BI Data Preparation Playbook, you will learn how to do so with Power Query. First, you’ll learn when Power Query is the right tool for the job, and how to navigate the Power Query editor. Next, you’ll explore how to add data transformation steps and access the underlying query code. Finally, you’ll discover how to fix errors and go even further using Python and R. By the end of this course, you'll feel completely comfortable using the Power Query Editor.
Enroll now

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by Eugene Meidinger, who is recognized for their work in data preparation and analytics
Explores industry-standard data preparation techniques using Power Query
Provides hands-on practice in data transformation and query optimization
Suitable for learners with basic data manipulation experience looking to enhance their Power BI skills
Requires proficiency in Power BI and a foundational understanding of data modeling concepts
May benefit learners pursuing a career in data analytics or business intelligence

Save this course

Save Power BI Data Preparation Playbook to your list so you can find it easily later:
Save

Activities

Coming soon We're preparing activities for Power BI Data Preparation Playbook. These are activities you can do either before, during, or after a course.

Career center

Learners who complete Power BI Data Preparation Playbook will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data analysts use their skills to make data-driven decisions. Cleaning and preparing data can be a huge part of the job. This course helps build a foundation by teaching you the fundamentals of data preparation in Power Query. This course can help you prepare for the role by teaching you the Power Query Editor, how to add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Data Engineer
Data engineers must prepare data to be used by data scientists and other analysts. This course can help you lay a strong foundation as a data engineer by teaching you the Power Query Editor, how to add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Business Analyst
Business analysts investigate data to help businesses make better decisions. This course may be helpful as it teaches you how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Data Scientist
To be successful as a data scientist, you must have an understanding of data preparation. This course may be helpful as it teaches you how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Database Administrator
Database administrators may use this course to learn about data preparation in Power Query. The course covers how to use the Power Query Editor, add data transformation steps, fix errors, and more. This course can help you prepare for this role by laying a solid foundation in data preparation.
Data Architect
Data architects may use this course to gain an understanding of data preparation in Power Query. The course covers how to use the Power Query Editor, add data transformation steps, fix errors, and more. This course can help you prepare for the role by giving you a firm foundation in data preparation.
Information Systems Manager
This course may be useful to information systems managers, as it teaches data preparation in Power Query. You will come to understand the Power Query Editor, how to add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Statistician
Statisticians may use this course to learn about data preparation. This course covers how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and more. This course can help you prepare for this role by teaching you how to clean, prepare, and analyze data in Power Query.
Machine Learning Engineer
Machine learning engineers may find this course helpful as it teaches data preparation in Power Query. You will learn how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Data Visualization Analyst
This course teaches data preparation in Power Query, which may be useful to data visualization analysts. You will learn how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Software Engineer
This course may be useful to software engineers as it teaches data preparation in Power Query. You will learn how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
IT Manager
This course may be helpful to IT managers as it teaches data preparation in Power Query. You will learn how to use the Power Query Editor, add data transformation steps, fix errors, and more. This course can help you prepare for the role by teaching you how to clean and prepare data for use in various applications.
Computer Systems Analyst
Computer systems analysts who work with data may find this course useful. You will learn data preparation in Power Query. You will learn how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Operations Research Analyst
Operations research analysts who work with data may find this course useful. You will learn data preparation in Power Query. You will learn how to use the Power Query Editor, add data transformation steps, access the underlying query code, fix errors, and even go further by using Python and R.
Financial Analyst
This course may be useful to financial analysts as it teaches data preparation in Power Query. You will come to understand the Power Query Editor, how to add data transformation steps, access the underlying query code, fix errors, and more.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Power BI Data Preparation Playbook.
Provides a comprehensive overview of data analysis techniques and best practices using Power BI. It covers data modeling, data wrangling, visualization, and reporting, making it a valuable resource for both beginners and experienced users.
Focuses on data modeling and analysis using Power BI. It covers star schema design, data aggregation, and performance optimization, making it a great choice for those interested in building scalable and efficient data models.
Provides a practical, step-by-step guide to Power Query, covering data source connections, data transformations, and advanced techniques. It is suitable for both beginners and intermediate users looking to enhance their Power Query skills.
Offers a collection of ready-to-use recipes for common data analysis tasks in Power BI. It covers data manipulation, visualization, and report creation, making it a handy reference for quick solutions.
Offers a comprehensive overview of Power BI for beginners and non-technical users. It covers all aspects of using Power BI, from data import to report creation, making it a great reference for those who need a clear and accessible guide.
Provides a practical approach to data preparation using Power Query. It covers data cleansing, transformation, and integration techniques, making it a useful guide for those looking to improve the quality of their data before analysis.
Offers a step-by-step guide to data modeling in Power BI. It covers data structure design, relationships, and optimization techniques, making it a good choice for those who want to build robust and efficient data models.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Similar courses are unavailable at this time. Please try again later.
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser