Power BI: Integrating AI and Machine Learning

Introduction

• The power of Power BI
• What you should know
• Overviewing AI and machine learning types
• Defining dimensionality
• Utilizing the Power BI ecosystem and Azure
• Configuring R in Power BI Desktop
• Introducing the course project

1. Configuring Power Query and the Data Model

• Utilizing AI in the ETL framework
• Configuring parameters
• Analyzing dataset statistics and distributions
• Configuring separate error logs for existing datasets
• Running Vision algorithms
• Utilizing Text Analytics algorithms
• Leveraging AI and the star schema
• Adjusting DateTime fields for lags

2. Analyzing a Single Variable

• Configuring aggregations and dimensionality
• Filtering options
• Calculating DAX measures
• Challenge: Single variable
• Calculating rolling averages
• Utilizing binning to create histograms
• Summarizing statistics
• Splitting a category with small multiples
• Leveraging violin plots
• Solution: Single variable

3. Measuring Relationships between Variables

• Visualizing relationships with scatter plots
• Accessing the Analytics pane
• Calculating correlations
• Visualizing correlations
• Adding clustering to existing visuals
• Calculating best fit line
• Utilizing the outlier detection visual
• Calculating outliers
• Contextualizing outliers
• Challenge: Multiple variables
• Solution: Multiple variables

4. Utilizing AI Visuals to Ask What-If Questions

• Determining key drivers with decomposition tree visual
• Leveraging the Q&A visual
• Utilizing parameters to model what-if scenarios
• Discovering key insights with the Key Influencer visual
• Challenge: AI visuals
• Solution: AI visuals

5. Analyzing Time Series Data

• Organizing time series analysis
• Adding forecasting from the Analytics pane
• Leveraging anomaly detection
• Utilizing ARIMA forecasting
• Incorporating seasonality through TBATS forecasting
• Analyzing predictions vs. actuals
• Challenge: Time series analysis
• Solution: Time series analysis

6. Creating and Sharing Analysis

• Designing a consolidated view for sharing
• Uploading and sharing in the Power BI service
• Configuring quick insights
• Challenge: Shared view
• Solution: Shared view

Conclusion

• How to learn ML and AI in Power BI