Data modelling is the backbone of meaningful analytics, and this session focused on helping participants design strong, logical data models in Power BI using a real-world hospital patient records case study đ.
đ§ Understanding Power BI Data Modelling Fundamentals
The session began with an introduction to fact tables and dimension tables, explaining how transactional data (facts) and descriptive data (dimensions) work together to support analysis.
Participants learned why unique identifiers (primary keys) are critical in dimension tables and how they connect to foreign keys in fact tables to create reliable relationships đ.
A key takeaway was that Power BI models should be driven by data structure, not just reporting requirementsâensuring scalability and accuracy as business questions evolve.
đ Establishing Correct Relationships
Participants practiced creating relationships between tables, with strong emphasis on:
⢠Many-to-one relationships (many records in the fact table, one record in the dimension table)
⢠Avoiding ambiguous or incorrect relationship types
⢠Understanding that column names donât need to match, as long as the values align correctly
This helped reinforce logical thinking and reduced common modelling mistakes that can lead to incorrect results.
Related Offerings
đ Creating and Using a Date Table
To enable time-based analysis, the session included a walkthrough on creating a date table using DAX đď¸.
Participants learned how to:
⢠Build a reusable date dimension
⢠Link multiple date fields (order, required, shipped dates) to a single date table
⢠Prepare the model for time intelligence calculations
This step is essential for trends, comparisons, and performance analysis over time.
đĽ Hands-On Hospital Data Modelling Exercise
Using a detailed hospital dataset, participants worked through a practical lab exercise that involved:
⢠Importing five Excel sheets
⢠Cleansing and validating data
⢠Using a data dictionary to identify correct keys
⢠Connecting patient, encounter, and procedure tables logically
The exercise encouraged participants to think like data modellers, not just Power BI users, strengthening their analytical mindset đĄ.
đ¤ Collaborative Review and Learning
After completing the exercise, participants shared their progress and challenges. Common issuesâsuch as difficulty identifying relationships or connecting patient dataâwere reviewed and clarified.
This collaborative feedback helped reinforce best practices and build confidence in applying data modelling concepts independently.
đ Key Takeaways
By the end of the session, participants were able to:
⢠Design clean fact and dimension tables
⢠Identify and apply primary and foreign keys correctly
⢠Build many-to-one relationships confidently
⢠Create and integrate a date table for time analysis
These skills form a strong foundation for advanced DAX, visualization, and certification preparation, and are essential for building professional Power BI solutions.
⨠Final Thought:
Strong dashboards start with strong data models. Mastering relationships, keys, and structure allows Power BI users to unlock accurate insightsâespecially in complex domains like healthcare.
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