Practice Set 1:
Objective: Power BI Desktop, Cloud Service and End to End Workflow
Use Case: Design dashboard with basic set of visualizations and deploy to
Power BI Cloud Service
Source: Trips Log Entries (Excel Workbook - Lans Transport Corp)
Analytics: Develop a dashboard to show top level brief overview of Transport
Corp data using aggregated KPIs, Trends, Geo Distributions and Filters.
Dashboard: Transport Dashboard
KPIs for Total Miles, Revenue, Cost
Revenue vs. Miles by Shipping State [Trend]
Revenue vs. Miles by Shipping City [Map]
Total Trips vs. Trips by Trip Types
Percentage of Trips by Shipping State
Revenue Miles vs. Total Miles
Practice Set 2:
Objective: Visualizations, Configuring Extended Properties and Data Calculations DAX - Introduction
Use Case: Design dashboard to make use of Power BI DAX formulas to perform calculations.
Source: Shipping Categories and Shippers (Open Data - Northwind OData) and Lans Transport Corp.
Analytics: Develop a dashboard to analyze scheduled deliveries of loads. Use correlations across measures. Implement drill downs and reference lines.
Dashboard: Delivery Analysis
Revenue Miles vs. Total Miles by Category
Add Analytical Lines
Tips by Delivery Status by Shipper (Row Context)
Enable Drill Down / Drill Up Capabilities
[Drill Down by Level, Hierarchical Drill Down, Select Drill Down] [Record View vs. Data View]
Shipping Costs vs. Revenue by Category
Create a Hierarchy on Location, Default Time Hierarchy
Practice Set 3:
Objective: Combination visualizations for correlated value columns.
Use Case: Design dashboard to make use of Power BI DAX formulas and perform calculations.
Source: Shipping Categories and Shippers (Open Data - Northwind OData) and Lans Transport Corp.
Analytics: Create bucketed categories to represent value measures on categories axis. Use scatter plot to identify outliers or outperformers.
Dashboard: Delivery Analysis
Trips by Shipping Days binned by Trip Type (Create Table)
Delivery Days vs. Due Days
Delivery Days vs. Due Days by DestinationCity
KPIs for Cost Per Miles, Revenue Per Miles, On Time Deliveries, Avg. Miles Per Trip (Set Context)
Practice Set 4:
Objective: Data Transformations
Use Case: Design an audit dashboard. Make use of Power BI Power Query [M].
Source: Trips Check Points (for Target) and Transport Corp (for Actual).
Analytics: Use Query Editor to perform data modeling by applying transformations. Manage relationships.
Dashboard: Checkpoints Analysis
Target vs. Actual Checkpoints Audit
Target vs. Actual Checkpoints by Week
Detailed Visualizations for Selected Audit
Cross Table - Checkpoints by Trip Type by Shipper
Practice Set 5:
Objective: Data Transformations Cont.
Use Case: Design a dashboard to analyze the trend of admissions into state universities.
Source: USA State University Admissions
Analytics: Use Query Editor to perform data modeling by apply transformations like:
Append Data
Split Data
Column Formatting
Fill Columns
Transpose Table
Pivot / Unpivot
Merge Join
Conditional Columns
Index Columns
Summary Tables
Practice Set 6:
Objective: Advanced Visualizations
Use Case: Design a dashboard to analyze the trend of admissions into state universities.
Source: USA State University Admissions
Analytics: Use expressions and filters to build custom visualizations.
Dashboard: Applications Analysis
Total Applications vs. Target Trend by State
Total Application by State Geo Dashboard
Tabular presentation of universities and funds
Percentage of Applications by Race
Dashboard: Universities Analysis
Top 10 Universities by Applications
Top 10 Universities by Applications with and without Special Grants
Bottom 10 Universities by Applications
Percentage of Applications vs. Universities’ Fund Allocations
Practice Set 7:
Objective: Advanced features of Power BI Cloud Service
Source: Google Analytics
Ad hoc analytics with Power BI Q&A
Feature, Favorite and Dashboards Settings
Dashboard Notifications and Alerts
Get data from Google Analytics and customize pre-loaded visualizations
Practice Set 8:
Objective: Advanced features of Power BI Desktop Client
Source: Transport Corp Data
Integrate Custom Visualizations and Create Sand Dance Visualization
Use shapes and symbols to increase report readability
Category Options, Summarizations, Show Blank Categories and Filters
Folder as a Source
Practice Set 9:
Use Case: Top Down and Bottoms Up Analysis to identify shipping costs Leakages
Source: Superstore Sales
Analytics: Build a set of visualizations to identify underlying outliers and flip the same set of visualizations to perform Bottom Up Analysis.
Top Down Analysis:
Shipping Costs by Order Priority - Bar Chart
Shipping Costs by Shipping Mode - Funnel Chart
Shipping Costs by Customers - Scatter Plot
Transactional view of underlying data
Bottom Up Analysis:
Duplicate above dashboard and change interactions
Replace Transactional View Donut and Scatter Plot with treemap
Practice Set 10:
Use Case: Value and Volume Based Analysis on hospital records to analyze Charges vs. Patients Inflow
Source: Country wide hospital inpatients records
Analytics: Build a set of visualizations linked to dynamic measures to flip analytics on user demand.
1. Dashboard
Create KPIs of Total Charges and Trends on Hospital Type and Categories
Create Geo Distribution of Hospitals
2. Hospital Analysis
Stacked Trend of Hospitals by State by City and by Category
3. Hospital Search
Details View and Slicers for Hospital Type, Category, State and City
DAX Expression - DynamicMeasure = IF(
FIRSTNONBLANK(AnalysisSetting[AnalysisSetting],TRUE())="Inflow"
,SUM(InpatientRecords[ Total Discharges ]),SUM(InpatientRecords[ Total
Payments ] ))
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