Power Query Bootcamp
via Noble Desktop
Affiliated with Course Report
Create repeatable data-preparation steps in Noble Desktop's Power Query Bootcamp. The course covers importing, cleaning, reshaping, and combining information, with attention to applied steps and refresh behavior. You practice turning a raw dataset into a structure that can be used for analysis without repeating the same cleanup manually.
- Format
- Live or Self-paced
Choose how you learn
Compare formats, then explore the details for your choice.
Enrollment and course access are provided by Noble Desktop.
Is this course right for you?
Knowledge equivalent to the Excel Bootcamp is expected. Choose this course when data preparation is the main challenge. Compare the Excel Bootcamp if you first need stronger spreadsheet foundations before developing repeatable Power Query transformations.
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Summary
Learn to use Power Query to clean, transform, and organize data for analysis. Working directly within the Power Query interface, you'll apply structured transformations, reshape datasets using tools such as Pivot, Unpivot, and Transpose, and combine data from multiple sources through appending and merging.
The course also covers creating grouped summaries, conditional columns, and columns from examples to enrich your data. You'll finish by learning how to organize and manage queries effectively using applied steps, duplication, dependencies, and refresh behavior.
Prerequisites
Participants should have knowledge equivalent to our Excel Bootcamp.
Topics included
Curriculum
What you'll learn
- Navigate the Power Query interface, understand the data analysis process, and work with Power Query options, applied steps, and refresh behavior.
- Clean and transform data by filtering rows, removing and reordering columns, changing data types, splitting and merging columns, and applying text cleanup techniques.
- Create structured transformations using grouping, conditional columns, date and duration calculations, and columns generated from examples.
- Reshape datasets using Pivot, Unpivot, Transpose, and split-to-rows techniques to support analysis and reporting.
- Combine data from multiple sources by appending tables, worksheets, and CSV files, and merging data using inner and anti joins.
- Organize and manage queries by duplicating and referencing queries, handling errors and values, removing duplicates and blank rows, and working with query dependencies.
Course syllabus
Getting Started with Power Query
- The Data Analysis Process
- What Is Power Query?
- The Power Query Interface
- Power Query Options & Settings
- One – Extracting
- Two – Transforming
- Three – Loading
- Four – Refreshing
- Benefits of Power Query
Transpose, Pivot, and Un-Pivot
- Transformations Overview
- Introduction to Transforming Data
- Removing Rows by Filtering Data
- Removing, Renaming & Reordering Columns
- Loading Your Transformations
- Applied Steps
- Saving Transformations
- Data Type Transformations
Combining Data from Two or More Data Sets
- Relationships
- Appending Two Tables
- Appending Multiple Tables
- Query Organization
- Appending Multiple CSVs
- Appending Data with Different Column Headers
- Merging Tables
- Merging via Composite Columns
- Inner Joins
- Right & Left Anti Joins
- Appending Multiple Worksheets
Duplicating and Parameters
- Duplicate & Reference Queries
- Remove Duplicates
- Deleting Queries
- Replacing Errors & Values
- Removing Top/Bottom Rows
- Using First Row as Headers
- Removing Blank Rows
Steps, Groups and Dependencies
- Transformation Steps Level 1
- Splitting Columns
- Merging Columns
- Trim, Clean, and Changing Case
- Transformation Steps Level 2
- Filling Down
- Sorting
- Extracting
- Math Calculations
- Unpivot
- Pivot
- Transpose
- Split Columns into Rows
- Group By
- Grouping by Dates/Times
- Date/Duration Calculations
- Conditional Columns
- Columns from Examples
- Extracting from Data Sources
- Getting Data from Excel
- Getting Data from CSV
- Getting Data from PDF
- Getting Data from Websites
What's included
- Free course retake within one year to refresh the material and gain practice.
- Class recordings
Stated by the provider. Confirm what your tuition covers before enrolling.
Schedule & enrollment
Find dates that fit your schedule, then book on Noble Desktop.
All class times are Eastern (ET).
-
Dates
Class time
Starts at 10am ET
Final session ends at 5pm ET
Attend
In-person or live online
-
Dates
Class time
Starts at 10am ET
Final session ends at 5pm ET
Attend
In-person or live online
Confirm current dates and availability on Noble Desktop before booking. Enrollment opens in a new tab.
Self-paced course
Learn through recorded lessons on your own schedule.
This course is available for 30 days. You can choose when to start your access period. Once you activate, you will have 30 days to complete it (access the course materials, quizzes, projects and videos). You may request one extension of seven (7) days. Other extension requests will be evaluated on a case-by-case basis. Videos are not downloadable.
- Tuition
- $499
- Course length
- 6 hours
- Schedule
- On your schedule
Enroll with Noble Desktop
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This course teaches students how to prepare and manage data using Power Query through a structured, step-by-step approach. Participants will learn to apply data transformations, reorganize datasets with pivoting and reshaping tools, and combine information from multiple files and tables.
The course also emphasizes building summarized views with grouping and conditional logic, creating new columns from examples, and maintaining organized queries through duplication, applied steps, dependencies, and data refresh processes.
Self-paced prerequisites
Participants should have knowledge equivalent to our Excel Bootcamp.
Self-paced curriculum
What you'll learn self-paced
- Navigate the Power Query interface, understand the data analysis process, and work with Power Query options, applied steps, and refresh behavior.
- Clean and transform data by filtering rows, removing and reordering columns, changing data types, splitting and merging columns, and applying text cleanup techniques.
- Create structured transformations using grouping, conditional columns, date and duration calculations, and columns generated from examples.
- Reshape datasets using Pivot, Unpivot, Transpose, and split-to-rows techniques to support analysis and reporting.
- Combine data from multiple sources by appending tables, worksheets, and CSV files, and merging data using inner and anti joins.
- Organize and manage queries by duplicating and referencing queries, handling errors and values, removing duplicates and blank rows, and working with query dependencies.
Self-paced syllabus
Getting Started with Power Query
- The Data Analysis Process
- What Is Power Query?
- The Power Query Interface
- Power Query Options & Settings
- One – Extracting
- Two – Transforming
- Three – Loading
- Four – Refreshing
- Benefits of Power Query
Transpose, Pivot, and Un-Pivot
- Transformations Overview
- Introduction to Transforming Data
- Removing Rows by Filtering Data
- Removing, Renaming & Reordering Columns
- Loading Your Transformations
- Applied Steps
- Saving Transformations
- Data Type Transformations
Combining Data from Two or More Data Sets
- Relationships
- Appending Two Tables
- Appending Multiple Tables
- Query Organization
- Appending Multiple CSVs
- Appending Data with Different Column Headers
- Merging Tables
- Merging via Composite Columns
- Inner Joins
- Right & Left Anti Joins
- Appending Multiple Worksheets
Duplicating and Parameters
- Duplicate & Reference Queries
- Remove Duplicates
- Deleting Queries
- Replacing Errors & Values
- Removing Top/Bottom Rows
- Using First Row as Headers
- Removing Blank Rows
Steps, Groups and Dependencies
- Transformation Steps Level 1
- Splitting Columns
- Merging Columns
- Trim, Clean, and Changing Case
- Transformation Steps Level 2
- Filling Down
- Sorting
- Extracting
- Math Calculations
- Unpivot
- Pivot
- Transpose
- Split Columns into Rows
- Group By
- Grouping by Dates/Times
- Date/Duration Calculations
- Conditional Columns
- Columns from Examples
- Extracting from Data Sources
- Getting Data from Excel
- Getting Data from CSV
- Getting Data from PDF
- Getting Data from Websites