
Introduction to the course and what we will be covering in the course
Load data into Power BI desktop from Excel and open the Query Editor to preview your data. Explore transforming data, promoting headers, and setting data types via the applied steps.
Explore Power BI query editor transformations, including using the advanced editor and M script, filtering data, changing data types, renaming and removing columns, and applying steps to load updates.
Learn to analyze employee tenure in Power BI by calculating length of service, creating department statistics (average, max, min), and using cross filtering to view employee lists.
Create salary groupings with a conditional column in the Power BI query editor. Use a matrix to count employees per salary range and analyze by gender and department.
Explore advanced transformations in the Power BI query editor, including merge with one-to-many relationships, append, custom calculations, and group by for invoice summaries by customer.
Use the merge function in the Power BI query editor to bring in related data with a left outer join on the employee ID, enabling name and department lookups.
Learn how to merge Power BI query editor tables to create an employee KPI table, using left outer and inner joins, and apply aggregation to count courses and sum costs.
Explore data quality across columns with visualization tools in the query editor, review diagnostic results from data refreshes, and cleanse a flawed table into a well-formatted one.
Discover how the power bi query editor assesses data quality, uses previews and diagnostics to reveal behind-the-scenes steps, and guides cleaning a messy excel data file.
Cleanse a data file in Power BI query editor by removing top rows and grand totals, promoting headers, filtering totals, and unpivoting years into year and sales for matrix report.
A brief introduction to the section on connecting to different data sources.
In this lesson we learn how to connect to a SQL database. We show how to access SQL tables and how to import the tables into Power BI.
In this lesson we cover how to load data into Power BI from Excel files.
In this practical activity you are able to practice loading data from a csv file into Power BI.
In this lesson we learn how to access data that is on the web and load it into Microsoft Power BI Desktop. Please note that data must be in an HTML table format for Power BI to access the data.
In this practical activity you will connect to a web data source and import the data into Power BI
This lessons shows how to load an XML file into Microsoft Power BI
JSON is a common format for transferring data between systems, especially on the Internet. In this lesson we review how to load JSON data into Power BI
Data sets that are loaded into the Power BI service can also be used as sources for new reports. In this lesson we review how to access and load data from the Power BI service.
Explore data flows in the Power BI service, show how data flow mirrors the query editor in Power BI desktop, and note pro or premium per user license requirements.
Explore Power BI service data flows to import and transform CSV data in a pro license workspace, then use the data flow as a source in Power BI Desktop.
The conclusion to the course video
This course contains the use of artificial intelligence.
Every lesson in this course is written, created and recorded by me. AI is used only to help produce supporting images and written materials around the lessons.
Most Power BI reports fail before a single chart is drawn. The data arrives in three files with different column names, the dates are stored as text, and half the rows are duplicates. This course is about that half of the job.
You will work entirely in the Power BI Query Editor: connect to a source, shape it, clean it, and save the steps, so that next month's file loads the same way in one click.
WHAT YOU WILL BUILD
Basic transformations - filter rows, change data types, remove and reorder columns, and add calculated columns
Advanced transformations - merge two tables on a matching column, append separate files into one table, group and summarize, and write custom calculations
Conditional rules - categorize your data with IF logic in the Query Editor, without touching DAX
Data cleansing - find and fix broken data with Query Editor Diagnostics, before it reaches your model
Connect to data sources - SQL Server, CSV and text files, web pages, XML, JSON and published Power BI datasets
Power BI Service dataflows - move your queries into the Service so a whole team reuses the same cleaned data
Every section sets a practical activity and then walks through the answer on video, and eleven training data files mean you are working on exactly the data I am.
MEET YOUR INSTRUCTOR
I have been training business people to work with data since 2008, and publishing on Udemy since 2013. I now have 16 live courses, more than 450,000 enrolments and more than 139,000 reviews, averaging 4.6. This course is rated 4.6 from 4,235 ratings.
I specialise in teaching business users the analysis methods behind the tools - Microsoft Excel, Copilot in Excel, Microsoft Power BI, Looker Studio and Amazon QuickSight. I teach the analysis, not just the software.
WHAT STUDENTS ARE SAYING
"Step by step process allowed me to understand stuff immensely"
"I have learned a lot about power BI on this learning and I now have a better understanding about it"
"I had basic PBI knowledge, this course helped me to improve my current skills. Professional, understandable and clear communication with a lot of great examples which can be used for my work on daily basis. Thank you !!!"
Ready to stop rebuilding the same import every month? Start with the first transformation and see how much of your reporting time you get back.