Building Power BI Reports

Introduction

The Power BI interactive dashboards are created to tell a story through data with a collection of visuals.

Steps to Build an Interactive Dashboard:

Import data by connecting to various data sources (Excel, SQL, SharePoint, etc.).
Transform data Use Power Query Editor to clean and shape the data.
Create Relationships between tables using keys (e.g., Customer ID, Product ID).
Add Visualizations by Dragging and dropping visuals from the visualization pane to your report canvas.
Use Slicers, Filters and drill-through pages to allow user-driven exploration.
Set Up Navigation with bookmarks and buttons to create an app-like experience.

Tips for Interactivity:

To achieve interactivity, use slicers for date ranges, categories, or regions. Enable drill-down and drill-through for detailed analysis. Use tooltips to show contextual information when hovering over visuals.

Using Visuals: Tables, Charts, Maps, etc.

Power BI offers a wide variety of visuals for clarity and insight which helps to communicate your data story effectively. Choosing the right visual is crucial as it leads to building effective reports.

Visual Type	Use Case Example
Table/Matrix	Displaying detailed transactional or tabular data.
Bar/Column Charts	Comparing values across categories.
Line Chart	Showing trends over time (e.g., sales per month).
Pie/Donut Charts	Displaying proportions in a dataset.
Map Visuals	Visualizing geographic data.
Card/KPI	Highlighting key metrics (e.g., Total Sales).
Gauge	Showing progress toward a goal.

Tips for Effective Visual Design:

Limit the number of visuals per page.
Use consistent colors and labels.
Add data labels only when necessary.
Group related visuals to tell a focused story.

DAX (Data Analysis Expressions)

DAX is the formula language for calculations and data analysis in Power BI. It helps create calculated columns, measures, and custom aggregations.

Basic DAX Functions:

DAX Function	Purpose	Example
SUM()	Adds all values in a column	SUM(Sales[Revenue])
AVERAGE()	Calculates the average of values	AVERAGE(Sales[Revenue])
COUNT()	Counts rows	COUNT(Sales[OrderID])
IF()	Conditional logic	IF(Sales[Revenue]>1000, “High”, “Low”)
CALCULATE()	Modify filter context	CALCULATE(SUM(Sales[Revenue]), Region=”East”)
FILTER()	Returns a table that represents a subset	FILTER(Sales, Sales[Revenue]>500)

Types of DAX Calculations:

Calculated Columns: Created in the data model, row-by-row basis.
Measures: Aggregated values used in visuals.

Conclusion

Whether you’re a business analyst, data professional, or a beginner in data visualization, mastering these core concepts will elevate your reporting skills in Power BI.

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Building Power BI Reports