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Rana Tehseen
Business/Data Analyst
Global Data Genius - Faisalabad, Pakistan
خلاصہ
I am Rana Muhammad Tehseen, a Certified Data Analyst, Business Analyst and Statistician from Pakistan, currently completing my bachelor's degree in statistics with a CGPA of 3.17/4.00. I specialize in data visualization and reporting with Power BI, Excel, Google Spreadsheet and have completed the Google Advanced Data Analytics professional course. My experience includes working as a Data Administrator and business Analyst and creating insightful projects in bank loan application analysis, sales management/analysis and Healthcare Analysis. Additionally, I have a Mini MBA in Marketing and am proficient in tools like Python, SPSS, Minitab, and Excel. I offer data analysis and interactive dashboards through the company, Global Data Genius.
پراجیکٹس
Sales Analysis Dashboard
Road Accident Analysis Dashboard
Ecommerce Store Sales and Order Analysis (Vrinda Store)
Coffee Shop Sales Management
Bank Loan Application Management Analysis
تجربہ
Business/Data Analyst
Global Data Genius
اگست ۲۰۲۳
- موجودہ
| Faisalabad, Pakistan
Role and Responsibilities:- Over 1 year of experience at Global Data Genius.- Skilled Business Analyst focused on strategic decision-making through data analysis.- Combines analytical skills with business understanding.- Identifies opportunities for improvement and growth.- Conducts in-depth analysis.- Collaborates with cross-functional teams.- Delivers actionable insights through reports and presentations.- Proficient in Excel, SQL, Python & R, and Power BI.- Proven track record of optimizing business performance with data.- Excellent communication skills.- Results-driven approach.- Valuable asset to any organization.
Data Administrator
Oxford School System Syedwala Distt Nankana Sb
فروری ۲۰۲۰
- اپریل ۲۰۲۱
| Buchay Key, Pakistan
Job Description:
As a Data Administrator at Oxford School System, I was responsible for managing and maintaining comprehensive data records for both students and staff. My role involved ensuring the accuracy and reliability of various datasets, which included names, grades, attendance, salaries, expenses, and overall management details.
Key Responsibilities:
Data Management:
Maintained detailed records of all students and staff, including personal information, academic performance, and attendance.
Handled financial records, including staff salaries and school expenses, ensuring all entries were precise and current.
Ensuring Accuracy:
Conducted thorough reviews and double-checks of all data entries to ensure accuracy and up-to-date information.
Implemented verification processes to maintain the reliability of the school's data, supporting consistent and dependable record-keeping.
Improving School Operations:
Provided accurate student information to school leaders, aiding in effective decision-making for class planning, resource allocation, and parent communications.
Contributed to the overall operational efficiency of the school by maintaining organized and accurate data systems.
Achievements:
Successfully kept track of all student and staff details, ensuring a high level of data integrity and reliability.
Enhanced the decision-making process for school leaders by providing accurate and timely information.
Improved the overall management of school operations through meticulous data administration.
Conclusion:
My role as a Data Administrator at Oxford School System was pivotal in maintaining the integrity and accuracy of essential school data. By ensuring reliable information, I supported better operational decisions and contributed to the overall success of the institution.
تعلیم
Coursera ( Michigan State University) (Online)
سرٹیفیکیشن,
Google Advanced Data Analytics Specialization, Foundation Of Data Science, Get Started With Python, Go Beyond The Number: Translate Data Into Insights, The Power Of Statistics, The Nuts And Bolts Of Machine Learning
مکمل
2024
From Coursera (Online) (https://www.coursera.org/account/accomplishments/specialization/certificate/5V6QQ65FRVZQ)
<div><p data-sourcepos="5:1-5:121">This project is an interactive dashboard that provides a comprehensive analysis of sales data, leveraging Excel and Power BI for visualization and analysis. The dashboard offers insights into key performance indicators, sales trends, customer behavior, and product performance. It is designed to assist businesses in making data-driven decisions and optimizing sales strategies.</p>
<h3 data-sourcepos="7:1-7:21"><strong>Key Features:</strong></h3>
<ul data-sourcepos="9:1-10:119">
<li data-sourcepos="9:1-9:124"><strong>Sales Overview:</strong> Presents a summarized view of total sales, profit, quantity sold, number of orders, and profit margin.</li>
<li data-sourcepos="10:1-10:119"><strong>Sales Analysis:</strong> Examines sales trends over time, identifies peak sales periods, and analyzes sales performance by region, category, and product.</li>
<li data-sourcepos="11:1-11:118"><strong>Customer Analysis:</strong> Provides insights into customer demographics, purchase patterns, and customer lifetime value.</li>
<li data-sourcepos="12:1-12:146"><strong>Product Analysis:</strong> Evaluates product popularity, profitability, and sales performance to optimize inventory management and marketing efforts.</li>
<li data-sourcepos="13:1-14:0"><strong>Interactive Visualizations:</strong> Utilizes charts, graphs, and maps to effectively communicate findings and enable interactive exploration of the data.</li>
</ul>
<h3 data-sourcepos="15:1-15:24"><strong>Technical Stack:</strong></h3>
<ul data-sourcepos="17:1-19:49">
<li data-sourcepos="17:1-17:77"><strong>Excel:</strong> Used for data manipulation, analysis, and initial visualization.</li>
<li data-sourcepos="18:1-18:102"><strong>Power BI:</strong> Employed for creating interactive dashboards with advanced visualization capabilities.</li>
<li data-sourcepos="19:1-19:49"><strong>SQL (Optional):</strong> If applicable, SQL was used to extract and transform data from a relational database.</li>
</ul>
<h3 data-sourcepos="21:1-21:21"><strong>Requirements:</strong></h3>
<ul data-sourcepos="23:1-27:0">
<li data-sourcepos="23:1-23:147"><strong>Data Set:</strong> A comprehensive dataset containing sales information, including customer details, product information, order dates, and quantities.</li>
<li data-sourcepos="24:1-24:105"><strong>Analytical Skills:</strong> The ability to interpret data, identify trends, and draw meaningful conclusions.</li>
<li data-sourcepos="25:1-25:115"><strong>Data Visualization Skills:</strong> Knowledge of creating effective charts and graphs to communicate findings clearly.</li>
<li data-sourcepos="26:1-27:0"><strong>Technical Proficiency:</strong> Familiarity with Excel, Power BI, and SQL (if applicable) for data manipulation, analysis, and visualization.</li>
</ul>
<h3 data-sourcepos="28:1-28:17"><strong>Outcomes:</strong></h3>
<ul data-sourcepos="30:1-30:87">
<li data-sourcepos="30:1-30:87"><strong>Data-Driven Insights:</strong> Uncovers valuable insights into sales performance, customer behavior, and product trends.</li>
<li data-sourcepos="31:1-31:179"><strong>Optimized Decision Making:</strong> Provides a valuable tool for businesses to make informed decisions regarding marketing strategies, inventory management, and customer acquisition.</li>
<li data-sourcepos="32:1-33:0"><strong>Enhanced Business Performance:</strong> Contributes to improving sales, profitability, and overall business efficiency.</li>
</ul>
<h3 data-sourcepos="34:1-34:25"><strong>Additional Notes:</strong></h3>
<ul data-sourcepos="36:1-39:0">
<li data-sourcepos="36:1-36:156">The dashboard can be further customized by incorporating additional data sources, refining analysis techniques, and creating more advanced visualizations.</li>
<li data-sourcepos="37:1-37:94">Consider using conditional formatting to highlight key trends and anomalies within the data.</li>
<li data-sourcepos="38:1-39:0">Explore the use of interactive features, such as drill-down capabilities and filtering options, to allow users to explore data in more detail.</li>
</ul></div>
<div><p data-sourcepos="5:1-5:462">This project is an interactive dashboard developed in Excel to provide a comprehensive analysis of road accidents. It offers valuable insights into various aspects of road safety, including accident frequency, severity, contributing factors, and trends over time. The dashboard leverages data visualization techniques to present complex information in a clear and understandable manner, enabling stakeholders to make informed decisions for improving road safety.</p>
<h3 data-sourcepos="7:1-7:21"><strong>Key Features:</strong></h3>
<ul data-sourcepos="9:1-10:50">
<li data-sourcepos="9:1-9:124"><strong>Dashboard Overview:</strong> Provides a summarized view of total casualties, fatalities, serious injuries, and slight injuries.</li>
<li data-sourcepos="10:1-10:50"><strong>Casualty Analysis:</strong> Breaks down casualties by vehicle type, road type, road surface, location, and time of day.</li>
<li data-sourcepos="11:1-11:125"><strong>Trend Analysis:</strong> Compares current year (CY) casualties with previous year (PY) casualties and visualizes monthly trends.</li>
<li data-sourcepos="12:1-12:103"><strong>Filter Panel:</strong> Allows users to filter data based on accident date, location, and light conditions.</li>
<li data-sourcepos="13:1-14:0"><strong>Data Visualization:</strong> Utilizes charts, graphs, and maps to effectively represent data and identify patterns.</li>
</ul>
<h3 data-sourcepos="15:1-15:21"><strong>Requirements:</strong></h3>
<ul data-sourcepos="17:1-18:117">
<li data-sourcepos="17:1-17:98"><strong>Excel:</strong> Proficiency in Excel is essential for data manipulation, analysis, and visualization.</li>
<li data-sourcepos="18:1-18:117"><strong>Data Set:</strong> A comprehensive dataset containing road accident information, including location, time, vehicle type, road conditions, and casualty details.</li>
<li data-sourcepos="19:1-19:105"><strong>Analytical Skills:</strong> The ability to interpret data, identify trends, and draw meaningful conclusions.</li>
<li data-sourcepos="20:1-21:0"><strong>Data Visualization Skills:</strong> Knowledge of creating effective charts and graphs to communicate findings clearly.</li>
</ul>
<h3 data-sourcepos="22:1-22:17"><strong>Outcomes:</strong></h3>
<ul data-sourcepos="24:1-27:0">
<li data-sourcepos="24:1-24:117"><strong>Data-Driven Insights:</strong> Uncovers valuable insights into road accident hotspots, contributing factors, and trends.</li>
<li data-sourcepos="25:1-25:152"><strong>Informed Decision Making:</strong> Provides a valuable tool for policymakers, traffic engineers, and law enforcement to implement targeted safety measures.</li>
<li data-sourcepos="26:1-27:0"><strong>Enhanced Road Safety:</strong> Contributes to reducing the number of road accidents and improving overall road safety.</li>
</ul>
<h3 data-sourcepos="28:1-28:25"><strong>Additional Notes:</strong></h3>
<ul data-sourcepos="30:1-33:0">
<li data-sourcepos="30:1-30:156">The dashboard can be further customized by incorporating additional data sources, refining analysis techniques, and creating more advanced visualizations.</li>
<li data-sourcepos="31:1-31:94">Consider using conditional formatting to highlight key trends and anomalies within the data.</li>
<li data-sourcepos="32:1-33:0">Explore the use of interactive features, such as drill-down capabilities, to allow users to explore data in more detail.</li>
</ul></div>
Ecommerce Store Sales and Order Analysis (Vrinda Store)
<div><p data-sourcepos="5:1-5:355">This project provides a comprehensive analysis of ecommerce store sales and order data, utilizing Excel to uncover valuable insights and inform data-driven decision-making. By leveraging advanced Excel functions and formulas, the analysis explores key metrics such as sales trends, customer behavior, product performance, and order fulfillment efficiency.</p>
<h3 data-sourcepos="7:1-7:21"><strong>Key Features:</strong></h3>
<ul data-sourcepos="9:1-14:0">
<li data-sourcepos="9:1-9:97"><strong>Data Cleaning and Preparation:</strong> Ensures data accuracy and consistency for reliable analysis.</li>
<li data-sourcepos="10:1-10:146"><strong>Sales Analysis:</strong> Examines overall sales trends, identifies peak sales periods, and analyzes sales performance by product category and region.</li>
<li data-sourcepos="11:1-11:179"><strong>Customer Behavior Analysis:</strong> Delves into customer demographics, purchase patterns, and customer lifetime value to understand customer preferences and identify target markets.</li>
<li data-sourcepos="12:1-12:155"><strong>Product Performance Analysis:</strong> Evaluates product popularity, sales velocity, and profitability to optimize inventory management and marketing efforts.</li>
<li data-sourcepos="13:1-14:0"><strong>Order Fulfillment Analysis:</strong> Assesses order processing time, shipping efficiency, and customer satisfaction to identify areas for improvement in the supply chain and logistics.</li>
</ul>
<h3 data-sourcepos="15:1-15:21"><strong>Requirements:</strong></h3>
<ul data-sourcepos="17:1-21:0">
<li data-sourcepos="17:1-17:98"><strong>Excel:</strong> Proficiency in Excel is essential for data manipulation, analysis, and visualization.</li>
<li data-sourcepos="18:1-18:173"><strong>Data Set:</strong> A comprehensive dataset containing ecommerce store sales and order information, including customer details, product information, order dates, and quantities.</li>
<li data-sourcepos="19:1-19:172"><strong>Basic Understanding of Business Metrics:</strong> Familiarity with key business metrics such as sales, revenue, profit, customer acquisition cost, and customer lifetime value.</li>
<li data-sourcepos="20:1-21:0"><strong>Analytical Skills:</strong> The ability to interpret data, identify trends, and draw meaningful conclusions.</li>
</ul>
<h3 data-sourcepos="22:1-22:17"><strong>Outcomes:</strong></h3>
<ul data-sourcepos="24:1-27:0">
<li data-sourcepos="24:1-24:126"><strong>Data-Driven Insights:</strong> Uncovers actionable insights to inform strategic decision-making and optimize business operations.</li>
<li data-sourcepos="25:1-25:132"><strong>Improved Business Performance:</strong> Provides recommendations for enhancing sales, customer satisfaction, and overall profitability.</li>
<li data-sourcepos="26:1-27:0"><strong>Enhanced Data Literacy:</strong> Develops skills in data analysis and visualization.</li>
</ul>
<h3 data-sourcepos="28:1-28:25"><strong>Additional Notes:</strong></h3>
<ul data-sourcepos="30:1-32:0">
<li data-sourcepos="30:1-30:154">The project can be further customized by incorporating additional data sources, refining analysis techniques, and creating more advanced visualizations.</li>
<li data-sourcepos="31:1-32:0">Consider utilizing pivot tables, charts, and other Excel tools to effectively communicate findings and insights.</li>
</ul></div>
<div><ul class="ehMmWHUVwxcgtWqtpnQYUeHKNsrxIiCIoQGtU
">
<li>
Associated with <strong>Global Data Genius</strong>
</li>
<li>
<ul class="ehMmWHUVwxcgtWqtpnQYUeHKNsrxIiCIoQGtU
">
<li>
<em><strong>Project Overview:</strong></em>Conducted a detailed analysis of retail sales data for a coffee shop with three branches to derive actionable insights and enhance business performance.<em><strong>Key Insights:</strong></em>Sales variation by day of the week and hour of the day.Identification of peak sales times.Monthly sales revenue tracking.Comparison of sales across different store locations.Average order value calculation.Identification of best-selling products by quantity and revenue.Sales variation by product category and type.<em><strong>Benefits for the Client:</strong></em>- Optimized Operations: Insights on peak times and sales variations help in better staffing and inventory management.- Revenue Growth: Identifying best-selling products and understanding customer spending behavior aids in targeted marketing and promotions.- Strategic Planning: Monthly revenue trends and location-based performance data support informed decision-making for expansion and resource allocation.<em><strong>Related Projects:</strong></em>- Restaurant Chain Revenue Analysis: Analyzed sales data across multiple locations to improve menu offerings and pricing strategies.- Retail Store Performance Dashboard: Created an interactive dashboard to track sales, inventory, and customer demographics for a clothing retailer.- E-commerce Sales Optimization: Conducted data analysis to enhance online sales strategies and customer retention for an e-commerce platform.These projects demonstrate my ability to leverage data analysis for business optimization, making me a valuable asset for clients seeking to enhance their business performance through data-driven insights.<strong>(We also created all these projects using Excel or Google Sheets, Power BI, and programming languages such as Python and R for handling large datasets).</strong>
</li>
</ul>
</li>
</ul></div>
<div><h3>Project Summary: Bank Loan Application Management</h3>
<p><strong>Overview:</strong></p>
<ul>
<li>This project involves the creation of an interactive and comprehensive dashboard for managing and analyzing bank loan applications. It provides insights into various key metrics, facilitating informed decision-making for financial institutions.</li>
</ul>
<p><strong>Key Features:</strong></p>
<ol>
<li>
<p><strong>Total Loan Applications:</strong></p>
<ul>
<li>Total loan applications: 38.58K</li>
<li>Month-to-date (MTD) applications: 4.31K</li>
<li>Month-over-month (MOM) growth: 6.91%</li>
</ul>
</li>
<li>
<p><strong>Financial Metrics:</strong></p>
<ul>
<li>Total funded amount: $435.8M</li>
<li>MTD funded amount: $54.0M</li>
<li>MOM growth in funded amount: 13.04%</li>
<li>Total amount received: $473.1M</li>
<li>MTD amount received: $58.1M</li>
<li>MOM growth in amount received: 15.84%</li>
</ul>
</li>
<li>
<p><strong>Interest Rates and Debt-to-Income (DTI) Ratios:</strong></p>
<ul>
<li>Average interest rate: 12.05%</li>
<li>MTD interest rate: 12.36%</li>
<li>MOM growth in interest rate: 3.47%</li>
<li>Average DTI: 13.33%</li>
<li>MTD DTI: 13.67%</li>
<li>MOM growth in DTI: 2.73%</li>
</ul>
</li>
<li>
<p><strong>Loan Applications Analysis:</strong></p>
<ul>
<li>By month: Visual representation showing monthly trends in loan applications, peaking at 4.31K in December.</li>
<li>By term: Breakdown of loan applications by 36 months (10.34K) and 60 months (28.24K).</li>
<li>By state: Geographic distribution of loan applications across various states.</li>
<li>By purpose: Detailed categorization showing loan applications for credit cards (18.21K), home improvement (2.88K), small businesses (1.78K), and other purposes.</li>
<li>By employment length: Distribution of loan applications based on the applicant's employment length, with notable peaks at 10+ years (8.87K) and 2 years (4.38K).</li>
<li>By home ownership: Comparison of loan applications from renters (18.439K), mortgage holders (17.198K), and owners (2.838K).</li>
</ul>
</li>
<li>
<p><strong>Good and Bad Loans Analysis:</strong></p>
<ul>
<li>Good loans:
<ul>
<li>Total applications: 33.24K</li>
<li>Funded amount: $370.2M</li>
<li>Amount received: $435.8M</li>
<li>Good loan percentage: 86.18%</li>
</ul>
</li>
<li>Bad loans:
<ul>
<li>Total applications: 5.33K</li>
<li>Funded amount: $65.5M</li>
<li>Amount received: $37.3M</li>
<li>Bad loan percentage: 13.82%</li>
</ul>
</li>
</ul>
</li>
<li>
<p><strong>Loan Application Status:</strong></p>
<ul>
<li>Fully paid loans: 32.15K applications with $351.4M funded and $411.6M received.</li>
<li>Charged off loans: 5.33K applications with $65.5M funded and $37.3M received.</li>
<li>Current loans: 1.10K applications with $18.9M funded and $24.2M received.</li>
</ul>
</li>
<li>
<p><strong>Interactive Features:</strong></p>
<ul>
<li>Filters for grade and purpose of the loan, allowing users to drill down into specific segments and perform detailed analyses.</li>
<li>Dynamic visualizations including bar charts, pie charts, and geographical maps to provide intuitive and actionable insights.</li>
</ul>
</li>
</ol>
<p><strong>Conclusion:</strong> This Bank Loan Application Management dashboard provides a powerful tool for banks to monitor, analyze, and manage their loan portfolios effectively. It offers a holistic view of loan application trends, financial metrics, and risk assessment, enabling data-driven decisions to optimize loan performance and reduce default rates.</p>
<p>This project demonstrates proficiency in data analysis, visualization, and dashboard development, showcasing an ability to turn complex data into actionable business insights.</p></div>
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