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Bank Credit Card Recommendations

​The Mitron Bank Credit Card Analysis Project aimed to guide the bank in launching a new credit card line. Analyzing a dataset of 4000 customers from five cities, the project focused on online spending habits and demographics. Using Power BI, Python, and Excel, it provided detailed customer segmentation, insights into spending and demographic trends, and a data-driven interactive dashboard. Key results included customer segmentation clarity and actionable recommendations for customized credit card features and targeted marketing strategies. Continuous data analysis was advised for adapting to market changes. The project's success hinged on effectively presenting findings to stakeholders, particularly Mr. Bashnir Rover's team.

Power BI Projects

Business Insights 360

In the "Business Insight 360" Power BI project, we've harnessed data to create a set of comprehensive dashboards that provide invaluable insights into finance, sales, marketing, supply chain, and executive performance. Through the application of key performance indicators and data modeling techniques, we've unlocked the power of informed decision-making. This project has equipped us with the skills to deliver data-driven value to stakeholders and drive long-term business success.

Financial Reporting

The Power BI financial report offers a comprehensive view of a business's financial performance, including income statements, balance sheets, cash flow, aged trial balance, and revenue insights. It highlights key metrics like net profit, gross profit, expenses, assets, liabilities, and cash flow from various activities. Actionable insights include optimizing costs, improving profit margins, managing assets and liabilities, and enhancing cash flow. The aged trial balance reveals outstanding invoices and helps with receivables management. Revenue insights focus on sales, profits, and product/customer contributions. Overall recommendations include cost optimization, receivables management, prioritizing high-margin products/customers, and informed investment/financing decisions. This report serves as a valuable tool for informed decision-making and financial health enhancement.

Healthstat | Healthcare Analytics

In this healthcare analytics case study, we analyzed New York state hospital data for elective hip replacement surgeries in 2016 using Power BI. We identified key insights, such as the average cost per discharge and factors influencing length of stay and cost. Our interactive Power BI dashboard empowers stakeholders to explore these findings visually, aiding HealthStat in identifying hospitals with potential efficiency improvements. Notable influencers on costs and length of stay included illness severity, mortality risk, location (New York City), and patient disposition to skilled nursing homes. This analysis equips HealthStat with valuable information for informed decision-making and improved patient care.

DataSearch

DataSearch, an employee recruiting firm, utilized Power BI to analyze job market trends in the data science industry. Their findings spanned from 2017 to 2021 and provided crucial insights into job demand, preferred roles, and required skills. Notable revelations included a consistent rise in job postings, the prominence of roles like Data Engineers and Data Scientists, and an upward salary trend. The study also explored the correlation between specific skills and job titles, helping job seekers tailor their qualifications. By identifying the top industries and companies actively hiring data science professionals, the analysis offered valuable guidance for job seekers, employers, and educational institutions, enhancing their strategies in the dynamic data science job market.

HR Analytics Dashboard

Exciting HR Analytics project at Atlas Labs! Monitored key metrics, uncovered insights like a 16% attrition rate, dominated by Technology department. Majority aged 20-29, 2.7% more women, 8.5% non-binary, and highest average salary among White employees.

Monthly/Weekly Customer Retention Cohort Analysis

I embarked on a cohort analysis project using a superstore retail dataset, exploring customer behavior and business insights. Preprocessing, data modeling in Power BI, and DAX measures formed the foundation. Visualizations unveiled monthly and weekly trends, providing valuable insights for strategic

AD-HOC Requests | Consumer Goods Domain

Welcome to the Atliq Hardwares! In the fast-paced world of consumer goods, where data-driven decisions are paramount, Atliq Hardwares, an industry leader in computer hardware production, has recognized the need for quick and informed decision-making. To meet this demand, they are expanding their data analytics team with the goal of hiring junior data analysts who possess both technical expertise and essential soft skills.

SQL Projects

Maven eCommerce Database Analysis

In my ongoing "Advanced MySQL Data Analysis by Maven Analytics" course, I worked as an eCommerce Database Analyst for Maven Fuzzy Factory, an emerging online retailer. Our midterm project aimed to uncover actionable insights from the eCommerce database. Key findings included the vital role of Gsearch in driving growth, promising results from non-brand and brand campaigns, and the significance of mobile traffic. A/B testing revealed incremental revenue opportunities, and our website's overall performance improved, as reflected in higher session-to-order conversion rates. This project emphasized the power of data analysis in informing strategic decisions, enhancing user experience, and driving business growth.

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AIRBNB Outlier Detection and EDA

Analyzed Airbnb's European booking dataset, revealing room type trends, pricing influences, and cleanliness's impact on guest satisfaction. Outlier detection refined data, highlighting hygiene's role. Data-driven insights empower hospitality for exceptional guest experiences.

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Cohort Analysis on Online Retail Data

This project involves performing cohort analysis on retail data using SQL queries. Through categorizing customers based on their first purchase month, insights into customer behavior, retention rates, revenue trends, and lifetime value are extracted to inform business strategies and decisions.

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RFM Segmentation on Sales Data

In this project, I conducted exploratory data analysis (EDA) on sales data using SQL queries. Insights included best-selling products by year and month, revenue trends, and customer segmentation based on RFM scores. These findings inform decisions for marketing, inventory, and customer engagements.

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Green World Sales Performance | Excel Dashboard

The "Green World Sales Performance Metrics" dashboard provides a comprehensive overview of sales-related data. It includes analyses of total earnings and paid calls, highlights the top 5 consultants with sales revenue by month, and identifies highest, lowest, and average monthly revenues. It also offers insights into the percentage of paid and unpaid calls, training model fees by sales team, and enrolled courses by training level. Additionally, it showcases paid call duration statistics, advertising spend by channel, total sales by sales team, and top-performing consultants and training models. The dashboard allows for effective performance evaluation and decision-making within the Green World sales team.

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EXCEL Projects

Python Projects

Fandango EDA

The Fandango EDA Data Science Project critically examines potential biases in Fandango's movie rating system, particularly in light of its dual function as both a movie rating display platform and a ticket seller. Centered around 2015 data, the project leverages Jupyter Notebook, NumPy, Pandas, Matplotlib, and Seaborn to analyze and visualize data. A key focus is the possible conflict of interest, exemplified by a detailed case study on "Taken 3." Data was collected and prepared from various sources, including Fandango and other review websites, with a focus on data cleaning and normalization for accurate comparison. The project's exploratory data analysis involved delving into dataset structures and summary statistics, creating new columns for enhanced analysis. It featured a thorough comparison of Fandango's ratings against actual movie ratings, as well as a comparative review analysis with platforms like Rotten Tomatoes, Metacritic, and IMDB. The findings revealed notable discrepancies between Fandango’s displayed ratings and actual ratings, with Fandango consistently showing higher ratings, leading to an uneven distribution skewed towards positive ratings, in contrast to more balanced or critical distributions on other sites. The analysis of "Taken 3" highlighted how Fandango’s ratings could be misleading. Concluding, the project underscores the importance of critical evaluation of online rating systems, advocating for transparency and reliability, and advises consumers to refer to multiple sources for a comprehensive understanding of a film's quality.

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