Chitranshi Singh
Data Analyst Berlin, Germany
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SQL
Movie Rental Analysis
Analysis of customer database for a fictional movie rental company. The objective was to analyze rental transaction history, customer geographic distribution, and revenue models in order to make strategic recommendations for the company to transition to online movie rental streaming. Database querying skills such as filtering, summarizing & cleaning data, joining tables of data, subqueries, CTEs were performed in SQL. Key results were curated on an interactive Tableau storyboard.
Tools: PostgreSQL, Tableau, Excel
Python
Hotel Cancellation Analysis
Analysis of hotel booking data for a city hotel and a resort hotel. The objective was to predict the factors which contribute to hotel booking cancellations and provide data-driven recommendations to reduce cancellation rates. This could be used to optimize booking service, anticipate when cancellations will occur and ultimately maximize revenue. Exploratory visual analysis such as correlation heatmap, pair plots, catplots to name a few and advanced analytical approaches such as linear regression, K-Means cluster analysis, time series analysis were conducted in Python. Key results were curated on an interactive Tableau storyboard.
Tools: Python and relevant libraries (Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy), Jupyter Notebook, Tableau
Instacart Grocery Basket Analysis
Sales analysis of a large and complex data set consisting of more than 30M records for an online grocery store. The objective was to derive insights about buying trends and customer demographics in order to target the right customer profiles with appropriate marketing strategies. Analytical tasks such as data wrangling & subsetting, merging data, deriving new variables, grouping data & aggregating variables were performed in Python using Jupyter Notebook and Pandas library. Analysis methodology, key results and recommendations were summarized into a detailed Excel report.
Tools: Python and relevant libraries (Pandas, NumPy, Matplotlib, Seaborn, SciPy), Jupyter Notebook, Excel
Tableau
Influenza Season
Analysis of US government influenza data. The objective was to examine seasonality of the virus and location of vulnerable populations to provide recommendations to a medical staffing agency for the distribution of temporary medical staff to clinics and hospitals. The results helped to plan for the upcoming influenza season. Descriptive statistical methods such as standard deviation, variance, and correlation were applied to summarize and understand the data. Inferential statistical analysis via hypothesis testing was conducted and the test results were interpreted. Key results were curated on an interactive Tableau storyboard.
Tools: Python and relevant libraries (Pandas, NumPy, Matplotlib, Seaborn, SciPy), Jupyter Notebook, Excel
Excel
Video Game Sales Analysis
Analyze historical sales data of games that sold more than 10,000 copies spanning different platforms, genres, and publishing studios for a fictional video game company. The objective was to compare assumptions about historical regional sales with the reality of current market conditions to help understand how the company’s new games might fare in the market and develop a competitive go-to-market strategy. Analytical procedures such as data cleaning, grouping & summarizing data using pivot tables, descriptive analysis were conducted using Excel. A detailed Presentation about data insights was produced.
Tools: Excel