This hands-on, online instructor-led course is intended as a continuation of our introductory-level courses PL-300: Microsoft Power BI Data Analyst and/or Excel BI Tools: Power BI for Excel Users in Power BI. This course covers common intermediate-level tasks and some of Power BI’s most desirable new features.
Prerequisites
Before attending this course, students should have the general knowledge equivalent to what is covered in:
- PL-300: Microsoft Power BI Data Analyst or Excel BI Tools: Power BI for Excel Users.
At Course Completion
After completing this course, students will be able to:
- Import data from PDFs, regions of web pages, and collections of files
- Characterize data with data profiling
- Merge mismatched data sets with fuzzy matching
- Generate custom columns in Power Query
- Perform advanced data modeling
- Use Power BI time intelligence
- Work with custom scripts in R and Python
- Create KPIs and scorecards
- Use advanced report design techniques
- Use advanced dashboard design techniques
- Perform basic statistical analysis in Power BI
Course Outline
Module 1: Intermediate Power Query
- Importing from PDFs
- Finding data in web pages
- Getting tabular data
- Getting data by providing an example
- Importing the contents of a folder
- Using fuzzy matching to combine disparate data sets
- Creating custom columns in Power Query
- Common math & string operations
- M script
- Columns by example
Module 2: Intermediate Data Modeling
- Adding What-If Parameters
- Grouping and Binning
- Using Time Intelligence
- Generating DAX with Quick Measures
Module 3: Script Visuals
- Creating an R script visual
- Installing an R environment
- Creating a Python visual
- Installing a Python environment
Module 4: Advanced Report Design
- Using report themes
- Creating your own theme
- Conditional formatting in tables and matrices
- Using drillthrough in your reports
- Adding data-driven images
Module 5: Advanced Dashboard Design
- Using dashboard themes
- Using the KPI visual
- Using the Multi KPI visual
- Adding KPIs and trend analysis with DAX
- Strategies for adding KPIs to tables & matrices
- Importing from Excel data model
- Conditional formatting
- The DAX UNICHAR function
- Image embedding
Module 6: Analytics
- Characterizing your data
- Revisiting the data profiler
- Getting help from custom visuals
- Moving averages
- ARIMA
- Linear regression in R
- Time series forecasting in Python
