A Power BI dashboard showcasing advanced data visualizations with custom charts and interactive filters.

Stepwise Process on How to Apply Advanced Visualization in Power BI

Step 1: Load Data from Excel into Power BI
One of the first necessities for advanced visualization is having data structured. Consider that you have an Excel dataset on sales performance, with some of the following columns:
•Date: Sales date (format YYYY-MM-DD)
•Region: Sales region (North, South, East, West)
•Category of Product: Classification of product (i.e. Electronics, Clothing, Furniture, etc.)
•Total Revenue: Total sales revenue
•Margin: Percentage of profit
•Customer Segment: Type of customer (Retail, Wholesale, Online)
Load Data Steps:
1. Begin Power BI Desktop
2. From Home, press Get Data on Excel
3. Select and browse your Excel file
4. Load data into Power BI

Step 2: Apply Advanced Visuals in Power BI
Power BI has made available a number of advanced visual elements that can extend reports further down the reporting line. Let's look at some of them:
1. Decomposition Tree
- Splits a metric, for example, revenue into various different factors contributing to it.
- Allows one to perform root cause analysis and drill down into granularity.
Reach of Implementation
1. Pick Decomposition Tree visual from the Visualizations Pane.
2. Drop Revenue into the Analyze field.
3. Add Region, Product Category, and Customer Segment as breakdown fields.
4. Users can now interactively explore how different factors influence the revenue.

2. KPI (Key Performance Indicator) Visual
- For monitoring important key business metrics, using clear indicators of performance.
- Best used for actual against target visualizations.
Carry out:
1. Select visual KPI under Visualizations Pane.
2. Drop the Revenue under the Indicator field.
3. Set target value (the previous year's revenue or a goal of business), for example.
4. Designate Date as a trend axis since performance over time will be displayed.

3.Sankey Chart
-Presents how categories (for example, how income moves through regions) interact with each other.
-Best used to illustrate trends in dynamic data.
Implementation:
1.Download the Sankey Chart visual from Power BI Marketplace.
2.Put Region in Source and Product Category in Destination.
3.Add Revenue as a Weight field to indicate the strength of the flow.

4.Heat Maps for Geographic Analysis
- Illustrating data density spatially.
Perfect for regional sales, customer distributions and event tracking.
Implementation:
1.Select Map in the Visualizations Pane.
2.Add Region in Location.
3.Add Revenue in Size to indicate intensity.
4.Select Heat Map style to represent density.

5.Custom R and Python Visuals
This includes incorporating advanced statistical and machine learning models in Power BI.
Basic knowledge of either R or Python is required.
Implementation:
1.Select either R or Python visual.
2.Copy script (e.g., advanced trend forecasting using Python's matplotlib or R's ggplot2).
3.Execute the script to generate the pictorial visualization.

Enabling More Interactivity through Advanced Visuals

More than just the various types of visuals, interactivity lets users drill down into the data relating to the topic at hand. Here are some techniques:
1. Drill-Through Pages
•Users can click on any data point to open a detailed report to conduct further analysis.
•For example, clicking on a bar chart for a region's revenues opens up a report for the sales breakdown by city.
Implementation:
1.Open a new page in Power BI.
2.Add the visual on that page (i.e., a table showing sales by city).
3.Visualizations Pane → Format → Enable Drill-Through.
4.Select the field that needs to be used for the drill-through option (e.g., Region).

2.Bookmarks & Buttons for Customized Navigation
• Construct interactive accounts for users by allowing them to click on buttons to view a report.
• Users can toggle between the different representations of the report in just one click.
How to Implement:
1. Open View → Bookmarks Pane.
2. Set up different perspectives of the report.
3. Utilize a Button from the Insert tab and assign a bookmark action.
4. Users would now be able to navigate different views of the reports dynamically.

Conclusion
Power BI has advanced visualization techniques that not only improve data storytelling but also enhance user experience and deeper insights. Using decomposition trees, KPI indicators, Sankey charts, heat maps and interactive drill through features, businesses picture their reports as very powerful analysis tools.
How do I get this? Choosing the right visuals, interactive reports and performance optimization. Start experimenting with these advanced techniques to unbundle your Power BI dashboards!