Creating Insights
From Data Enthusiast to Data Analyst
Hi, my name is Vitor H. Ferreira, aiming to to connect with like-minded individuals, who are passionate about transforming raw data into actionable insights.
In God we trust. All others must bring data. – W. Edwards Deming
Why Data Analytics?
Data has the power to change the way businesses operate. It reveals patterns, predicts trends, and guides smarter decision-making. My goal is to harness that power to solve real-world problems. My journey is fueled by a love for numbers and insights, and a desire to contribute to data-driven decisions.
The Foundation:
Great Datasets
It all Starts with Great Data
Before we can analyze, visualize, or draw any conclusions, we need one thing: Data. Without meaningful datasets, learning data analysis would be like trying to solve a puzzle without any pieces. The availability of high-quality, real-world datasets has been instrumental in my learning process, helping me understand everything from basic statistics to more complex machine learning algorithms.
By working with diverse datasets, I’m able to practice real-world problem-solving and gain deeper insights into how data shapes business decisions. Datasets from platforms like Kaggle, data.world, and Statso provide the raw material for every project and analysis I do.
Tools That Power Insight
The Data Toolbox
SQL
SQL is the backbone of data manipulation and querying. It allows data analysts to retrieve, filter, and organize large datasets efficiently. Mastering SQL is crucial for accessing the exact information needed for deeper analysis and drawing insights from databases.
Python
Python is a versatile tool in the world of data analytics, allowing for powerful data processing, automation, and advanced statistical analysis. With libraries like Pandas and NumPy, Python makes it easy to manipulate and analyze data, while also enabling machine learning and data visualization.
PowerBI
Power BI is a business analytics tool that transforms data into interactive visualizations and dashboards. It’s perfect for sharing insights across teams and making data-driven decisions. Its simplicity combined with its robust visualization capabilities makes it a go-to tool for any Data Analyst.
Tableau
Tableau takes raw data and turns it into beautiful, easy-to-understand visualizations. It’s a favorite among analysts for creating dashboards that communicate complex data clearly to stakeholders, driving insights at a glance.
These are the tools I’m mastering. Together, they form a powerful data analysis toolkit. SQL retrieves and structures data, Python performs the heavy lifting with data processing and advanced analytics, and Power BI turns those insights into actionable visual reports. This combination equips a Data Analyst with everything they need to extract meaningful insights and deliver them in impactful ways.
The Learning Path
01
Foundations of Data Analysis
02
Exploring Data
03
Data Visualization
04
Advanced Analytics
Learning by Doing:
My Data Projects
Olist Marketplace Analysis
Tools
SQL – Python – PowerBI
Datasource
Kaggle
In this project, I structured Olist’s e-commerce data in SQL, analyzed sales trends and customer behavior, and built dynamic dashboards in Power BI. I also began incorporating Python for more advanced analysis…
11
Datasets
~100K
Orders
EDA
SQL SSMS
Visuals
PowerBI
Sharing My Insights
Through my blog, I document what I learn, the challenges I face, and the insights I gain from analyzing data. Whether you’re just starting or you’re a seasoned data pro, I hope these articles inspire and inform
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Hello World of Data Analysis
Welcome to my journey! My name is Vitor H. Ferreira, and I’m on an exciting path to becoming a data analyst. This is my first time creating something that truly aims to record my progress in a structured way—a place where I can share my learnings, solidify my understanding, and, hopefully, connect with others on…
Let’s get in touch!
Contact me and provide details about your inquiry. I will get back to you soon.