Connecting GitBash to GitHub(Step-by-step Guide)

michael akello — Fri, 03 Apr 2026 08:44:51 +0000

Getting started with GitHub and GitBash is key for any developer, Here is a quick guide to link the two for a windows O.S.

Initial Steps;

Install GitBash - https://github.com/LuxDevHQ/Data-Tools-Installation-Guide?tab=readme-ov-file#git-bash
Set Up a GitHub Account.
Create a personal Access Token in GitHub.

steps
1. click your Profile picture (Top Right)
2. Go to settings
3. Scrol to Developer settings
4. select personal access tokens
5. Click Token(classic)
6. Click generate new token(classic) -copy and save your token safely(you wont see it again).

open GitHub

create a Project directory.

$ mkdir GitLink

change directory into the created directory.

$ cd GitLink

initialize Git.

$ git init

configure your identity

$ git config --global user.name akellomichael
$ git config --global user.email michaelomondiakello@gmail.com

connect to your GitHub repository.

create a repository on GitHub, then link it:

$ git remote add origin https://github.com/akellomichael/GitHub_GitBash-Connection

Verify the connection:

$ git remote -v

Authenticate Using Your Token.

update the remote URL to include your username and token.

$ git remote set-url origin https://akellomichael:Git_Token@github.com/akellomichael/GitHub_GitBash-Connection

pull all commits(if any) from the remote repo:

$ git fetch origin

create your first file.

$ touch gitlink_doc.md
$ code gitlink_doc.md

Add some content via your default Editor, save and close the file.

Stage the changes.(Add all)

$ git add .

Commit your changes. - create a snapshot of your currently staged project.

$ git commit -m "First Draft"

push to Github

 $ git push --set-upstream origin master

subsequent pushes;

 $ git push

Hurray!! Your link was successful. GitBash linked to GitHub.

Understanding Data Modeling in Power BI: Joins, Relationships, and Schemas Explained

michael akello — Fri, 03 Apr 2026 08:31:20 +0000

What is Data Modeling?
Schemas, Relationships, and Joins (Overview)
SQL Joins.
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- FULL OUTER JOIN
- LEFT ANTI JOIN
- RIGHT ANTI JOIN
Power BI Relationships
- Cardinality (1:M, 1:1, M:M)
- Active vs Inactive Relationships
- Cross-Filter Direction
- Joins vs Relationships

1. What is Data Modeling?

According to IBM, data modeling is the process of creating a visual representation of an information system to show how data elements relate to each other.

Simply put:
Data modeling is the process of identifying, organizing, and defining the types of data a business collects—and how those data points relate.
It uses Diagrams, Symbols, and Table structures to show how data is captured, stored, and used.

Why Data Modeling Matters

A well-defined data model helps to:

Understand data requirements
Ensure proper structure for reporting
Align data with business goals

- Maintain data integrity and consistency

2. Schemas, Relationships, and Joins (Overview)

A database schema is a structural blueprint (tables, fields, keys) defining how data is organized, while relationships define how tables connect (e.g., foreign keys). Joins are SQL operations that combine data from these related tables. Together, they ensure data integrity and facilitate querying complex data structures.

These three concepts work together:

Schemas → The blueprint (tables, fields, keys)

Relationships → Logical connections between tables (via keys)

Joins → The method used to combine data from tables

3. SQL Joins.

Joins combine data from multiple tables using a common column (called a join key).

Example Scenario:
a school dataset with table Student joined to table Marks.

3.1 INNER JOIN

Returns only matching records from both tables.

Student ∩ Marks

    👉 Use case: Show students who have marks recorded.

3.2 LEFT JOIN (LEFT OUTER JOIN)

Returns all rows from the left table + matching rows from the right.

All Students + Matching Marks

👉 Use case: Show all students, even those without marks.

3.3 RIGHT JOIN (RIGHT OUTER JOIN)

Returns all rows from the right table + matching rows from the left.

All Marks + Matching Students

👉 Use case: Identify marks that don’t have a matching student record.

3.4 FULL OUTER JOIN

Returns all rows from both tables, matching where possible.

Students ∪ Marks

👉 Use case: Audit mismatches between datasets.

3.5 LEFT ANTI JOIN

Returns rows from the left table with no match in the right table.

Students NOT IN Marks

👉 Use case: Find students with no recorded marks.

3.6 RIGHT ANTI JOIN

Returns rows from the right table with no match in the left table.

Marks NOT IN Students

DEV Community: michael akello