Data enthusiast with a passion for decoding patterns and turning data into actionable insights.
My fascination with numbers and the stories, they reveal sparked my journey into data analysis. Even before the term "data analyst" entered my vocabulary, I was analyzing data for personal projects. This passion ignited a fire within me to explore the vast world of data analysis. My hunger for knowledge led me to online courses, YouTube tutorials, intensive boot camps, and independent research.
Now, I leverage this passion to transform complex data into actionable insights. As a data analyst, I delve into the world of information, uncovering patterns and trends that drive informed decision-making.
In this project I take raw housing data and transform it in SQL Server to make it more
usable and understandable for analysis
It reveals property value trends, identifies investment opportunities in growing
neighborhoods, and assesses the impact of external factors on the real estate market.
I analyzed British Airways reviews with Tableau, uncovering passenger sentiment trends by month and location. I even drilled down to aircraft-specific insights to help optimize their fleet. Interactive dashboards with dynamic filters empower users to find what matters most to them, driving data-driven decisions
In this project, I've included 10+ data analysis project show-casing my skills and experience in data analytics using Python's library.
Crafting dashboards and analyzing data, this project has increased my experience of Power BI and made of more capable of handling different type of data in different ways.
This project about Black-Friday-Sales-Prediction includes Data Exploration & Cleaning, Visualization, Data Preprocessing, and Model Building which includes Linear Regression, Ridge Regression, Decision Tree Regressor, Random Forest Regressor, Extra Trees Regressor and XGBRegressor
This analysis utilizes the "Adidas Sales Dataset" from Kaggle, which includes data on retailers, dates, region, product, total sales, unit sold, operating profit, sales method etc.
In summary, Adidias' success story involves strategic sales methods, product popularity, and regional variations. Whether you're a marketing professional or a fan of the brand, understanding these insights can be fascinating!
In this section, I showcase my journey learning SQL, from basic queries to advanced data manipulation techniques like joins, aggregations, and window functions.
Power BI allows me to create interactive data visualizations and dashboards that effectively communicate insights to stakeholders. I leverage this skill to transform complex data into clear and actionable stories.
MS Excel is my go-to tool for data cleaning and wrangling. I use its powerful formulas and functions to ensure my data is accurate and ready for further analysis.
Tableau empowers me to create clear and engaging data visualizations. I'm skilled in crafting a variety of charts and graphs, including bar charts, line graphs, heatmaps, and maps, enabling stakeholders to explore data independently and make data-driven decisions.
Python is a powerful tool in my data analysis arsenal. I leverage libraries like Pandas for data cleaning and manipulation, and NumPy for numerical computations. Using these libraries, I can efficiently handle missing values, outliers, and explore data through statistical analysis. Furthermore, I can create custom data visualizations using libraries like Matplotlib or Seaborn, allowing me to tailor visualizations to specific needs and uncover hidden patterns within the data.
As a data enthusiast with a knack for decoding patterns, I bring expertise in analytics, turning data into actionable insights. Let's unravel the stories hidden in numbers together.