Build a Customer Service Power BI Solution in Under 1 Hour (From Scratch!)

In this hands-on tutorial, Devin Knight demonstrates how to build a complete Power BI solution for customer service analytics in under 60 minutes. Designed for beginners and intermediate users, the video walks through the entire process—from raw data ingestion to building interactive dashboards—using a real-world customer service dataset.

🔍 Starting with the Right Questions

Devin begins by identifying key business questions to guide the solution:

• What is the average time to resolve support tickets?
• How many tickets are currently open?
• Which agents have the highest customer satisfaction scores?
• Which customers generate the most tickets?

📊 Understanding Metrics and Attributes

He explains the importance of separating metrics (facts) from descriptive attributes (dimensions):

• Metrics: Ticket count, resolution time, satisfaction score
• Attributes: Agent details, customer type, ticket status

📁 Data Preparation and Modeling

Using Power Query, Devin transforms a flat CSV file into a star schema model:

1. Agents Table: Extracted agent ID, name, and team
2. Customers Table: Extracted customer ID, name, type, and segment
3. Date Table: Created using a custom Power Query script
4. Tickets Table: Cleaned and trimmed to include relevant ticket data

🔗 Building Relationships

Relationships are established between the fact table (tickets) and dimension tables (agents, customers, dates) using one-to-many joins. Devin also demonstrates how to create hierarchies for better drill-down capabilities in reports.

📐 Creating DAX Measures

Several DAX measures are created to answer the initial business questions:

• Total Tickets: Count of all ticket rows
• Average Time to Close: Using AVERAGEX and DATEDIFF
• Open Tickets: Filtered by blank resolution values
• High Priority Tickets: Filtered by priority values ("Critical", "High")

📈 Building Reports

Devin builds four report pages to visualize the data:

1. Ticket Summary

• Card visuals for total, open, and high-priority tickets
• Bar and column charts for ticket status and priority
• Small multiples for ticket category by resolution
• Date slicer for time-based filtering

2. Tickets by Agents

• Bar chart showing average satisfaction by agent/team
• Clustered column chart comparing total vs. reopened tickets
• Stacked bar chart for average close time by agent and priority

3. Tickets by Customers

• Bar charts for ticket volume by customer segment and type
• Tree map for ticket submission channels
• Bar chart for average satisfaction by customer type

4. Open Tickets Overview

• Matrix visual showing open tickets by agent hierarchy and priority
• Decomposition tree for drilling into open tickets by category, priority, and status

🎯 Final Thoughts

Devin wraps up by encouraging viewers to explore Pragmatic Works’ Hackathons, which offer personalized training using the customer’s own data. This video serves as a practical guide for anyone looking to build a Power BI solution quickly and effectively.

Don't forget to check out the Pragmatic Works' on-demand learning platform for more insightful content and training sessions on Power BI and other Microsoft applications. Be sure to subscribe to the Pragmatic Works YouTube channel to stay up-to-date on the latest tips and tricks.