My Data Analytics Portfolio

MySQL & Power BI Project

Loan Analytics: Profit & Risk Insights

Analyzed 40k loans with MySQL, Power BI, DAX, and Excel. Applied advanced SQL (CTEs, window functions, dynamic SQL, stored procedures, correlation analysis) for data exploration and cleaning. Developed interactive reports, published to Power BI service. Set up gateway & shared reports via embed links & workspace apps.

Excel Project

Decoding Tesla’s Decade: An In-Depth Financial Analysis (2009-2023)

I analyzed Tesla’s financial performance from 2009 to 2023 using Excel, aiming to understand growth, profitability, and investment potential. Key skills developed include predicting cashflows, financial statement analysis, DCF analysis, ratio analysis, trend analysis, data integration, critical thinking, and project management.

Python Project

eCommerce Insights from Flipkart’s Sales Data

Explored 19k+ purchases to uncover sales drivers and online shopper behavior. Implemented NLP and TextBlob for sentiment analysis and wordcloud generation on product descriptions. Leveraged Pandas, NumPy, Matplotlib, Seaborn, NLTK for data cleaning, analysis, and visualization.

Python Project

Netflix Stock Data Analysis - Investing Insights, Patterns, Trends, Forecasting

Analyzing Netflix stock data to predict future performance and identify trends & seasonality. Techniques includes time series analysis, statistical tests, moving averages, daily returns, autocorrelation, and ARIMA forecasting.

Excel Project

From Tweets to Trends: An In-depth Analysis of Twitter Activity

This project analyzes Twitter activity using a dataset of 100k tweets. Applied descriptive statistics, correlations, Xlookup, pivot tables, conditional formatting. Through meticulous data cleaning and insightful analysis, it offers actionable insights for optimizing Twitter presence and content strategy.

Python Project

Cricket Sports Data Analysis

Leveraging Python’s Pandas and Plotly Express libraries, I analyzed data from the IPL cricket, uncovering insights into team performance, player statistics, match outcomes, toss analysis, and venue-specific trends.

Python Project

iPhone Sales Data Analysis

Analyzing iPhone sales data using Python and Jupyter Notebook. Includes data cleaning, calculates key statistics, identifies top-rated iPhones, visualizes data, conducts correlation analysis, and derives insights for pricing and marketing strategies.

Excel Project

Unlocking Guest Retention Secrets Through Hotel Booking Cancellation Analysis

Here I focuses on reducing hotel booking cancellations by analyzing guest booking data using Excel. It delves into various factors like guest demographics, room preferences, hotel types, and seasonal trends to uncover hidden patterns and cancellation triggers. Tools and Techniques: Power Query, Pivot tables, Descriptive statistics, Time series analysis.

Abhishek Mishra