DEV Community: Kamanda Bryan

Introduction to Schemas Data Modelling in Power BI.

Kamanda Bryan — Mon, 02 Feb 2026 19:52:01 +0000

Introduction:

Story time... This is the part where i jog your mind before delving into tech terms. Lets assume you worked in a university and you are required to collect data from different schools and departments,the same would involve different items like registration number,name,scores in different exams,year of study,the major...etc. Definately,this would be stored in different Excell sheets and workbooks. So,when analysing the data,how do you easily do it? Thats where PowerBi comes in. In my books,PowerBi is Excel on steroids since of its different capabilities.

Definition

Power BI is a business intelligence and data visualization tool developed by Microsoft that helps organizations analyze data and present insights in an interactive and meaningful way. It enables users to connect to different data sources, shape and model data, and build reports that support decision-making. Although Power BI is often associated with dashboards and visuals, the effectiveness of these reports largely depends on how the underlying data is modeled. Proper data modelling ensures that reports are accurate, performant, and easy to interpret.

In Power BI, data modelling involves structuring data into logical tables, defining relationships between them, and ensuring that business metrics behave correctly when analyzed.

Fact and Dimension Tables

A key principle in Power BI data modelling is the separation of data into fact tables and dimension tables.

Fact tables store measurable data related to business activities. In a university setting, a fact table might store student enrollment records, exam results, or fee payments. For example, an enrollment fact table could contain fields such as Student ID, Course ID, Semester, and Enrollment Count or Fees Paid. These tables tend to be large because they record events that occur repeatedly over time.

Dimension tables provide descriptive information that gives context to the facts. In the same university scenario, dimension tables could include Students, Courses, Departments, Lecturers, and Dates. A Student dimension might store details such as student name, gender, program, and year of study, while a Course dimension could include course name, credit units, and department. These tables allow users to analyze facts by different perspectives, such as enrollment by department or performance by course.

Star Schema

The star schema is the most commonly recommended schema for Power BI models. In this structure, a central fact table is directly connected to several dimension tables.

Using the university example, an Enrollment Fact table may sit at the center of the model and connect directly to Student, Course, Department, and Dates eg of joining etc. Each dimension has a single relationship with the fact table, creating a clear and simple structure.

This approach works well in Power BI because it simplifies how data is queried and analyzed. Report visuals such as “Total Enrollments by Department” or “Average Grades by Course” can be created easily without complex calculations.

Snowflake Schema

A snowflake schema is a more normalized version of the star schema, where dimension tables are broken down into multiple related tables.

In a university database, this might occur when Course information is split into separate tables for Courses, Departments, and Faculties, or when Location data is separated into Campus, City, and Country tables. Instead of linking the Enrollment Fact table directly to all descriptive data, some dimensions are linked through other dimensions.

While this structure reduces data duplication and is common in transactional systems, it introduces additional complexity in Power BI. Queries may require navigating through multiple tables, which can slow performance and make calculations harder to manage. For reporting purposes, Power BI generally performs better when these dimensions are flattened into a simpler star schema.

Relationships in Power BI

Relationships define how tables interact within the Power BI model. In most analytical scenarios, relationships follow a one-to-many pattern, where a single row in a dimension table relates to many rows in a fact table.

For example, one department can offer many courses, and each course can have many enrollment records. Defining these relationships correctly ensures that when a user filters a report by department, the related enrollments are accurately reflected. Poorly defined or ambiguous relationships can result in incorrect totals, such as duplicated enrollment counts or missing data in reports.

Importance of Good Data Modelling

Good data modelling is essential for both performance and accuracy in Power BI. A well-structured model allows Power BI to process and compress data efficiently, resulting in faster report interactions even when dealing with large volumes of university data.

Accurate modelling also ensures that analytical results reflect real-world relationships. For instance, calculating student performance by department or tracking enrollment trends over academic years requires a model that correctly represents how students, courses, and departments relate to one another. Additionally, a clean and logical model is easier to maintain and understand, especially when reports are shared across different university departments such as administration, finance, and academics.

Conclusion

Schemas and data modelling are central to effective Power BI reporting. By organizing data into fact and dimension tables, favoring star schemas over snowflake schemas, and defining clear relationships, analysts can build models that are both efficient and reliable. In contexts such as a university, where data spans multiple departments and systems, good data modelling ensures that Power BI delivers accurate insights that support informed planning and decision-making

Simplest GIT and GITHUB explanation.

Kamanda Bryan — Sun, 18 Jan 2026 09:40:14 +0000

Introduction

Lets say you and I decide to come up with one of the best recipes for pancakes. But instead of the obvious flour, water and oil, we choose to improve that recipe. And this is how we do it,if you make pancakes today, you write it down on a notebook and send a picture of the same to me ,I use the same recipe tomorrow and add my improvements. With time, there will be significant changes. Lets say we get to day 10. And notice the sugar is abit too much and somewhere along the way,one of us,added the amount. We simply go back to either, our notebooks or check the images shared and can notice who made the changes in the recipe.
So basically you have a local notebook and online copy of the same to do the same. In developers terms,the two tools are git and github.
Lets dive right into it. By definition,

GIT

A free, open-source, distributed version control system (VCS) that tracks changes in source code during software development, allowing teams to collaborate, manage different versions, revert to past states, and work offline efficiently with local repositories.

GITHUB

A web-based platform for hosting source code and facilitating collaboration and version control among software developers and other users.
Git is a tool, and GitHub is a service that uses that tool.

CREATING GITHUB ACCOUNT

To create a GitHub account, go to https://github.com/login, enter your email, choose a password and unique username, complete the puzzle verification, then enter the code sent to your email to finish signing up and access your dashboard. You can also use Google or GitHub Enterprise accounts for social sign-up if preferred.

DOWNLOADING GIT

To download Git, visit the official website at git-scm.com and select your operating system. The installation process varies slightly depending on whether you use Windows, macOS, or Linux.

Download the installer: Go to the official Git for Windows website and the download should start automatically.
Run the installer: Once downloaded, run the executable file (ending in .exe).
Follow the prompts: Click "Next" to accept most of the default settings, which are suitable for most users. The installer will install Git and Git Bash.

Simple commands

Verify: Open Command Prompt or PowerShell and type

git --version

Set your name:

git config --global user.name "Your Name"

git config --global user.name "Kamanda Bryan"

Set your email:

git config --global user.email "youremail@example.com"

git config --global user.email "kamandamulwa@gmail.com"

I think we dived way too deep,my bad,let me explain.
What we've done is verification or confirming whether the installation was successfull then setting the user name and email. Allow me to mention this guide for windows users,for linux users kindly visit https://git-scm.com/install/linux and https://sourceforge.net/projects/git-osx-installer/files/git-2.23.0-intel-universal-mavericks.dmg/download?use_mirror=autoselect for MacOs others kindly visit https://github.com/git-guides/install-git for guidance.
Back to Business,now that we've downloaded Git and GitHuB,let link them for ease of communication between the 2.

When you connect to a GitHub repository from Git, you need to authenticate with GitHub using either HTTPS or SSH(Secure Shell Protocol). And for this example,allow me to use SSH key,we are keeping it simple.
Find guide on adding SSH Key https://docs.github.com/en/authentication/connecting-to-github-with-ssh/generating-a-new-ssh-key-and-adding-it-to-the-ssh-agent

Push and pull

To push and pull code using Git, you interact with local and remote repositories via specific commands in your terminal or command prompt. The git push command uploads your local commits to the remote repository, while git pull downloads new commits from the remote and integrates them into your local branch.

How to push code from VS Code to GitHub

1.Using the VS Code GUI

Open your project in VS Code.
Open the Source Control panel: Click on the Source Control icon on the sidebar or press Ctrl+Shift+G.
Stage your changes: Click on the '+' icon next to each changed file to stage files individually, or click on the "Stage All Changes" icon at the top to stage all changes.
Commit your changes: Enter a commit message in the input box at the top of the Source Control panel. Press Ctrl+Enter to commit the staged files.
Push your changes: Click on the '...' button at the top of the Source Control panel, then select "Push" from the dropdown menu. If you are pushing to a new branch, select "Push to" and enter the branch name.

2. Using the VS Code terminal

Open the integrated terminal in VS Code: Use the shortcut Ctrl+` (Control + backtick) or navigate through View -> Terminal.
Stage your changes: Run the command:

git add .
3.Commit your changes:
Run the command:

git commit -m "Your descriptive commit message"
4.Push your changes:
To push to the main branch, run:

git push origin main
NOTE:To push to another branch, replace main with your branch name.

Steps to Pull Codes

Open your terminal or command prompt and navigate to your project directory.
Ensure you are on the correct branch (e.g., main or master) you want to update using the command:

git checkout <branch-name>

Run the git pull command to fetch and merge the latest changes from the remote repository into your current local branch:

git pull origin <branch-name>
In most cases, if your current branch is tracking a remote branch, you can simply run:

git pull