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Day 1: EASYTECH Academy #ExcelBootcampChallenge
Hello everyone! I'm Abdulazeez Abdulrahmon, and I've just kicked off the 10-day ExcelMastery challenge with EASYTECH Academy. I'm excited to enhance my data skills and master powerful Excel tools.
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Day 5 of my 10-day data analysis challenge is complete! Today, I used a bar chart to visualize product sales distribution and uncover key insights.
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“Day 5 of my Excel Challenge : I Created a sales chart 📊
POINTS TO NOTE:
Fashion Accessories dominate, while Health & Beauty needs attention.”
#Excel #DataAnalytics #easytechbootcamp #easytech365 #easy_p5
DAY 4 OF 10 DAYS DATA CHALLENGE WITH @easytech365
Today, I explored Conditional Formatting in Excel, a quick way to spot top performers & outlier.
I Highlighted "high sales" as values > 500 and low as those < 500 from the totals column
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Day 4 of my Excl Challenge:
I Highlighted high sales (500+) with conditional formatting for faster analysis and insight.
#Excel #DataAnalytics #DataVisualization #ExcelChallenge #easytechbootcamp #easytech365 #easy_p5
DAY 3 OF 10 DAYS DATA CHALLENGE WITH EASYTECH ACADEMY
Hii Friends!
I'm focusing on basic formulas in excel.
#Ride with me. 🚀
Basic formulas are necessary to draw conclusion. I'd be using just two today.
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Welcome to Day 3 of the Excel challenge — Calculating Total Sales & Average Order Value with Excel formulas
✅We used formulas to get the total sales and average order value in our data set👇👇
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✳️Then, I used the AVERAGE formula to find the average order value, which was £322.97.
I've attached a breakdown of how these formulas were applied. Many more formulas are out there, and I'll be exploring them as the challenge continues!
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We imported sales data into Excel and performed essential cleaning
✅ Removed duplicates
✅ Handled missing values
✅ Ensured consistency
Clean data drives accurate insights and decisions
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✅The data was converted into a structured Excel table and formatted for consistency.
This cleaning step creates a uniform dataset that's ready for analysis.
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Hii Friends, I'm Aanuoluwa Oluwayemi
I started a course in data analysis with @easytech365, and here am I to share a little bit of the progress I have made.
Walk with me though this 10 days challenge on an excel project.
Thank you
#easytechbootcamp, #easytech365, #Easy_p5
My name is Mr. Kehinde Bello now known as Mr. Drexller Tyrell kehinde Farouk.
Below is a screenshot dataset provided to work on.
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Hi Everyone!
This is Day 7 of 10-Day Data Challenge: Use of Advanced Formulas
💡 INDEX Function: is used to return a value in a given position in a dataset/table.
💡 VLOOKUP Function: is used to search for values in a vertical...
@easytech365
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Day 6 of 10 days Data Challenge: Creation of Pivot Tables and Charts
As an Analyst, I intend to draw insights from the given dataset using appropriate visualization tools.
💡 The branch with the highest sales was Branch C ($105,304),...
@easytech365 ,#easytechbootcamp ,
Hi!
Day 5 of my 10-day Data Challenge: Creating Charts💻📊📈
I created a bar chart depicting the product-wise sales distribution from the given dataset to reflect insights.
Watch out for Day-6!
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Hello!
Day 3 of 10 days Microsoft Excel Bootcamp: Use of Basic Formulas!
It's time to bring meaning to our Dataset. Data analysis gives insights and directions.
Let's start with:
🔶 Average Order Values
🔶 Total Sales
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Hi everyone ☺️,
I'm thrilled to announce that I will be participating in a 10 Days Bootcamp Data Challenge starting today, March 5th, and running until March 14th, 2025.
@easytech365
#Dataanalyst
#easytechbootcamp
#easytech365
8 of 10 Days Data challenge
Today's challenge is to Analyze sales trends over time
January: Sales were high at 116,291.868.
February: Sales dropped significantly to 97,219.374.
March: Sales recovered to 109,455.507.
@easytech365 #easytechbootcamp #easytech365
Day 7 of 10 Days data challenge,
Today i continue my data Analysis journey by exploring advanced formulas in excel. My challenge for the day is to work with three powerful functions: VLOOKUP, MATCH and INDEX.
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Day 6
As i go deeper into our data set, pivot tables is used to analyze our sales data set from multiple angles.
Actionable insight was extracted to inform decisions. It includes:
-Sales by city:
-Sales by gender:
-Sales by customer type
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