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JCars Logistics Power BI Business Intelligence Assessment

lincon omondi — Fri, 02 Oct 2026 17:29:09 +0000

Introduction

Jcars logistic is company dealing with cars in Kenya. The company came up with sample raw data to insight the business progress. From keeping track on the cars sold, the revenue, the car model with the higher and least purchase revenue in the company. To answer the key questions; how many cars sold in specific location, number of cars sold in total, sales rep with the most and least sales and the revenue of the cars sold; we will analyze the raw data.

Understanding the data.

Examining dataset is essential before working on it. Knowing the key aspect. Transforming my data to query after uploading to power BI. Categorizing my data from the columns and rows; transactions, people, location, vehicles, customer, measure and date.

Data cleaning

Here are the steps;

Promoting headers
From the incorrect headline of my dataset. I started by promoting headers; my first row as headline to create the difference between my heading and the rest of data.
Changing type of different columns
Changing the type of information in column into their unique type, example; the; text columns to text, date column to date and all numerical columns to number.
Numerical formatting
The use of percentages and whole number in currency. Applying the currency ambiguity and monetary values;

Correcting the negative recorded revenue.
changing the currency from the USD to KES "Kenya currency."

These are few steps I took to clean my raw data and duplicate my newly cleaned data for any inconvenience later.

Data modelling

_Data modeling in Power BI is the process of organizing data from different tables and defining how those tables relate to each other, so you can analyze the data correctly and build reports and dashboards. _

Building the data

visualizing the thoughts and understanding key columns to form the fact table and the dimensional tables before generating the primary and foreign keys.

Creating the facts table and dimension table from the queries.

Starting by duplicating my cleaned data and renamed it as fact table.
After duplication I reference the new queries from the original cleaned data. Reference queries are generally more efficient, especially if you’re building layered transformations.

Dim customers: customer name, customer type and customer age
Dim sales rep: sales rep
Dim location: region, county, city and branch
Dim vehicle: vehicle type, car model, vehicle year, fuel type, transmission and color
Dim date: order date
Dim lead source: lead source
Dim payment method: payment method and status

In each dimensional query I selected all the columns and removed the duplicates.

After the duplicate I added the index column from 1 so I can generate the primary keys.

After the process I came up with a cleaner relationship and merging of queries.

Analysis and Insights and Management tools

calculation of relevant question

key findings using Dax;

Total cars sold =sum (fact table [unit sold]
Total sales revenue =sum (fact table [units sold] * fact table [unit selling price]
Total cost =sum (fact table [unit sold] * fact table [unit cost]
Gross profit =[total sales revenue]- [total cost]
Gross profit margin =divide ([gross profit], [total sales revenue]

My final dashboard insight

The purpose of the dashboard is to bring clear analysis vision of the key data in simple way. It's a professional way to keep track and performance.
I used table slicers and charts to easily monitor and understand the trend without the spreadsheets.

Conclusion

Understand and visualizing the data is essential before any step.it helps you create or make good decision beforehand on it. Every data has different styles. with the help of questions also matter with accordance to which Dax formula you can use.

Getting Started With Excel For Data Analytics: From Basic To Data Cleaning & Analysis.

lincon omondi — Sun, 30 Aug 2026 00:15:17 +0000

Introduction.

Excel is a spreadsheet used for data collection, editing and analysis.
it can as well describe the workflow scheme of a specific data.

What you should know while leaning excel from excel basic;

Familiarizing with the excel interface
knowing from the workbook, worksheets and excel command ribbon

Excel command ribbon is a key navigation tool when using excel.
how to use each tool and its function.

The workbook is for organizing and data entry.

Here are components used;

1.cell -space within the highlighted boxes.

2.column - is the vertical part from your excel workbook.
(top to bottom)

3.Rows - is the horizontal part of your excel workbook.
(left to right)

Data cleaning

Data cleaning refers to correcting raw dataset to a well separate data.
It is advisable to separate two worksheets on a excel workbook from the original raw data and the newly formatted data.

Data cleaning is essential for removing duplicates, missing values and autocorrecting spelling mistakes.

Data Formatting

Data formatting is used to specify specific content within data, distinguish it and analyzing it making it easier to be read.
Specific components should be used in reference; like when using dates, monetary values can be formatted as currency.

freezing the row and column

Freezing is used to retain the marked header for easy comparison of the specific data within the freeze column.
It is essential in maintaining data context preventing scrolling confusion.it keeps header row visible while reviewing the records.

Formulas

The use of formulas is important aspect in relation to data accumulation records.
We execute formulas command to gain required combination arithmetic operations.
Every formula should start with =.
_example _

(=A1+B1) when looking for addition
(=A1-B1) when looking for difference

Conclusion

Excel is a powerful Microsoft tool used in everyday life to simplify and organize accurate data by formulating and analyzing using different excel skills.

Practical Understanding of GitHub Using {GIT And SSH}.

lincon omondi — Sat, 22 Aug 2026 20:43:15 +0000

Introduction.

First understanding the difference between git and GitHub. understanding how they relate and its functions.

Procedure

step 1: Downloading Git and sign up for GitHub account

use recommended setup and follow instruction given to install depending on the operating system on your computer.

Step 2: Configurations of Git

Tell git who you are and make sure it knows you.
Tell git your name and email by using the following commands;

git config --global user.name "Your Name" 2.git config --global user. Email "you@example.com"

step 3: Generating SSH key

The ssh key will be used to link your Git and GitHub.
when running the command it will generate two keys; private and public.
public key is used to pair files.
command used is;
ssh-keygen -t ed25519 -C "you@example.com"

step 4: Adding the public ssh key to GitHub

Identify your public SSH key from your Git and copy it.

Open you GitHub and go to settings.

Click on the _SSH and GPG keys and add new SSH key.

Fill the tittle with name and paste your key.

Add the key and verify your using Gmail account.

step 5: create local folder from your computer with data

Create folder from your file explorer with data.

Name your folder.

Go to git and use ls command to list files name to ensure the created file name is edited.

Step 6: Git repository

Use git commit -m "_your file name_ command to turn the folder to git repository so that you can push to GitHub.

Step 7: pushing the file to GitHub

Add origin to match your GitHub account and the file using
git remote add origin git@github.com:" _your GitHub username and your file name_

Since we created SSH key my git and GitHub are secure and connected.

Specify the folder and make it default before pushing by this command;
git branch

Use; git push -u to push your folder and put the passphrase if needed.

Refresh your GitHub page and confirm the uploaded files.

Things to note

Never share your private SSH key
Always your directories where the files were created

Conclusion.

GitHub is a social network used to upload files and projects from your local computer using git. you can access your project or make it public for people to access. understand each step to make it easier and make it a routine.

DEV Community: lincon omondi

JCars Logistics Power BI Business Intelligence Assessment

Introduction

Understanding the data.

Data cleaning

Data modelling

Building the data

Analysis and Insights and Management tools

My final dashboard insight

Conclusion

Getting Started With Excel For Data Analytics: From Basic To Data Cleaning & Analysis.

Introduction.

What you should know while leaning excel from excel basic;

Data cleaning

*Data Formatting *

freezing the row and column

Formulas

Conclusion

Practical Understanding of GitHub Using {GIT And SSH}.

Introduction.

Procedure

step 1: Downloading Git and sign up for GitHub account

Step 2: Configurations of Git

step 3: Generating SSH key

step 4: Adding the public ssh key to GitHub

step 5: create local folder from your computer with data

Step 6: Git repository

Step 7: pushing the file to GitHub

Things to note

Conclusion.

Data Formatting