Believer • Humanitarian •Data Analyst 📊 https://xitter.cf/t.co/6o7QTJjUTd
Lagos, Nigeria
Joined November 2020
- Tweets344
- Following236
- Followers226
- Likes1.6K
Adebare 🥰❤ retweeted
Congratulations to the 43rd Vephla Alliance Techies.🎉
We’re so proud of you all. ❤️
📷 Tag who you just spotted and send them some Congratulations 🎉🍾🎉
-Vephla University – at London, England
Adebare 🥰❤ retweeted
Dear UNEMPLOYED,
You're not a failure. You're not a mistake. You're not doing anything wrong. You're not unlucky, too
The course you studied is not the problem. Nothing is wrong with your CV. It's not your fault that you don't have any experience.
No, employers don't hate you.
It's just not your turn yet.
Soon, it'll be your turn and lines will fall into places beautifully for you
Adebare 🥰❤ retweeted
Being UNEMPLOYED is DEPRESSING. Let's PRAY for PEOPLE who are JOB hunting to find a JOB this DECEMBER and next YEAR!!!!!!!!!!
Adebare 🥰❤ retweeted
Data Analysts, Scientists with less than 100 followers, repost and drop your handles
Let’s do this again and grow together
👨🏾💻
Following everyone that engage.
Adebare 🥰❤ retweeted
Ranked #1 EdTech Startup of the Year! 🏆✨
We're transforming & empowering enthusiasts to succeed by helping them build the Tech skills needed to land Top Tech roles. 🚀
Get started at vephlauni.com
Thank you for being a part of this incredible journey! 🚀
Adebare 🥰❤ retweeted
Good morning my people.
Today, I want us to talk about the unsung hero of data analysis, DATA CLEANING!
Yep, the part we all secretly dread but absolutely can’t skip😂.
If you want your data to actually tell the truth, it’s got to be clean.
Here are 3 tips to keep you sane while you clean your data.
1. Tackle Missing Values: Think of missing values as ‘plot holes’ in your data story. Fill in the gaps with averages (for numbers) or most common values (for text). If they’re too wild to fix, remove it!
2. Remove Duplicates: Duplicates are like déjà vu, you don’t need to see them twice! Use Excel’s 'Remove Duplicates' or SQL’s DISTINCT to get rid of duplicates that mess up your data
3. Keep It Consistent: Make your data look like it belongs together! Standardize dates, currencies, and text formatting so you don’t end up with a chaotic mix. Trust me, your future self will thank you.😂
Do you have your own data-cleaning hack? Let’s hear it in the comments!
Share your story with the class!😂
#DataCleaning #DataTips
Adebare 🥰❤ retweeted
As part of my ongoing education @VephlaUni. I analyze the sales data of Cisco Group of Companies to assess their performance throughout the year.
Adebare 🥰❤ retweeted
I'm thrilled to share my very first LinkedIn post about my journey in Data Analysis 😊. As I continue to advance in my data analytics studies at @VephlaUni , I've had the opportunity to conduct an analysis on Netflix Cinematic Landscape Overview…
Adebare 🥰❤ retweeted
Stop using pie chart in your data visualization?
Why?
What is Pie chart, Pros, Cons and use cases
Have a good read 👨🏾💻;
But before you go, take a look at this picture, what do you notice?
ALT Image from theconversation.com
Adebare 🥰❤ retweeted
Data Analysis projects idea you should try:
1. Sales Performance Analysis: Analyze sales data to identify trends, seasonality, and factors affecting sales performance.
2. Customer Segmentation: Use clustering techniques to segment customers based on demographics, behavior, or purchase history.
3. Market Basket Analysis: Analyze transaction data to identify patterns of co-occurring products purchased together.
4. Sentiment Analysis: Analyze customer reviews or social media data to understand sentiment towards a product or service.
5. Churn Prediction: Build a model to predict customer churn based on historical data and customer characteristics.
6. Financial Forecasting: Forecast financial metrics such as revenue, expenses, or profits using time series analysis.
7. Supply Chain Optimization: Analyze supply chain data to optimize inventory levels, reduce lead times, or improve delivery performance.
8. Healthcare Analytics: Analyze healthcare data to identify trends, predict disease outbreaks, or optimize resource allocation.
9. Employee Turnover Analysis: Analyze HR data to understand factors contributing to employee turnover and develop retention strategies.
10. Climate Change Analysis: Analyze environmental data to understand the impact of climate change on various regions or ecosystems.