Sanjeet Jagdale
Data Nerd . Creativity . Learning
Data Analyst / Business Aanlyst
SKILLS
- SQL (SQL Server, MySQL)
- Excel (VLOOKUPs, Conditional Formatting, Pivot Tables, Dashboard)
- Data Analysis
- Web Scraping
- Microsoft Power BI (Interactive Dashboard, DAX)
- ETL (Extract, Transform, Load)
- Maths & Statics
- Communication
- Data Visualization (Storytelling)
PROJECTS
MUSIC STORE DATA ANALYSIS – Project (LinkedIn Challenge) – SQL
- As a budding data enthusiast, my “Music Store Data Analysis” project exemplifies my passion for uncovering insights through data-driven exploration. This project is where I delved into the world of music retail by leveraging SQL and a dataset from Kaggle. Through data analysis, I unearthed patterns and trends that shed light on customer behavior and product popularity, demonstrating my analytical capabilities in the field.
-Project Phases:
- Data Sourcing: The project’s journey began with the acquisition of a comprehensive dataset from Kaggle, encompassing valuable information about music store transactions, including customer details, product purchases, and sales records.
- SQL Analysis: Armed with SQL, I embarked on a journey to analyze the dataset. I formulated queries to unravel meaningful insights, gaining a deep understanding of customer preferences, popular music genres, and purchasing trends.
- Insightful Discoveries: My analysis led me to discover pivotal insights, such as the most popular music genres, frequently purchased products, most sales, and customer demographics.
-Key Insights from the Analysis:
- Genre Popularity: The project potentially revealed the most popular music genres among customers, which could be used to curate playlists and tailor marketing efforts.
- Top-Selling Products: Visualizations demonstrated the products that generated the highest revenue, offering valuable information for inventory management and marketing campaigns.
- Customer Segmentation: By examining customer demographics and purchase behavior, I potentially identified different customer segments, paving the way for targeted promotions and personalized experiences.
-Project Impact:
- The “Music Store Data Analysis” project is a proof to my learning and applying data analytics techniques. Through the power of SQL, I demonstrated my ability to transform raw data into actionable insights, showcasing my value in the field of data analysis. As a fresher, this project is a stepping stone towards establishing my credibility in the field, highlighting my ability to handle data and present meaningful findings to drive business success.
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COFFEE SALES DATA ANALYSIS – Personal Project – Excel
- The “Coffee Sales Data Analysis” project showcases my web scraping skills to unearth data. In this, I leveraged AI-tools to gather raw data from online sources, cleaned and structured it using Excel, and in an interactive and visually engaging dashboard within the familiar confines of Microsoft Excel.
-Project Phases:
- Web Scraping: The project journey commenced with the application of AI-powered web scraping tools. Employing advanced techniques, I extracted comprehensive coffee sales data from online platforms, ensuring a rich dataset that captured various aspects such as product details, pricing, quantity, and distribution.
- Data Refinement: Armed with the raw data, I refined and standardized it in Excel. This phase involved data cleaning, removal of duplicates, handling of missing values, and structuring the information into a coherent format ready for analysis.
- Interactive Excel Dashboard: Transforming refined data into actionable insights, I designed an interactive dashboard within Excel, deonstrating the power of data visualization without the need for specialized software. This dashboard facilitated comprehensive exploration of coffee sales trends and patterns.
-Key Features of the Dashboard:
- Geographic Insights: Dynamic bar chart provided a visual representation of coffee sales across different regions, enabling users to identify areas of high demand and potential expansion opportunities.
- Product Performance: Interactive visuals showcased the performance of various coffee products, shedding light on top-selling items and customer preferences.
- Sales Trends: Line graph portrayed sales trends over time, enabling users to identify seasonal patterns and evaluate the effectiveness of marketing campaigns.
- Interactive Filters: Users could interact with filters to refine their analysis based on specific criteria such as order date, Rost type name, quantity, and loyalty card.
-Project Impact:
- The “Coffee Sales Data Analysis” project demonstrates my Knowledge in leveraging technology for data acquisition, cleansing, and visualization. By weaving together AI-tool for web scraping, Excel for data manipulation and interactive dashboard design, I showcased my ability to create actionable insights from raw data. It serves as a Challenge to my knowledge to transforming data into actionable insights that empower businesses to make informed decisions and drive success.
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CAR INSURNACE POLICIES REPORT – Project (LinkedIn Challenge) – PowerBI
- The “Car Insurance Policies Report” stands as a testament to my proficiency in transforming complex datasets into actionable information. This project was a response to a challenging opportunity presented on LinkedIn, where I was tasked with analyzing a provided dataset related to car insurance policies. Leveraging Power BI, I build an interactive dashboard that convert data into coherent visualizations, enabling stakeholders to make informed decisions in the insurance domain.
-Project Phases:
- Dataset Exploration: The journey began with the exploration of a comprehensive dataset containing a wealth of information about car insurance policies. The dataset encompassed crucial details such as claim amount, household income, coverage zone, claim history, and car details.
- Data Transformation: To ensure the dataset was conducive to analysis, I applied various data transformation techniques using Power Query within Power BI. This phase involved data cleaning, joining relevant tables, handling missing values, and standardizing formats for consistency.
- Dashboard Design: With a refined dataset at hand, I embarked on the creation of an intuitive and interactive dashboard using Power BI’s visualization capabilities. The dashboard was designed to offer an insightful overview of key insurance metrics and trends.
-Key Features of the Dashboard:
- KPI’s : Interactive KPI’s provided an overview, allowing users to understand the key Insights.
- Claims Analysis: Visualizations showcased the severity of claims, Highlighting the top 5 car manufacturers and top 5 car models
- yearly Analysis: line chart displayed the distribution of claim amount by car year, revealing potential insights into pricing strategies and customer behaviors.
- Interactive Filters: Users could interact with filters to refine their analysis based on specific criteria such as car manufacturers, model and color, gender, marital statusand education of customers.
-Project Impact:
- The “Car Insurance Policies Report” effectively bridged the gap between complex data and actionable insights. By transforming raw data into visually appealing and easy-to-understand visualizations, the dashboard empowered stakeholders to make well-informed decisions regarding policy pricing, risk assessment, and customer engagement strategies. This project exemplifies my ability to extract meaningful insights from diverse datasets and present them in a compelling and user-friendly format. With this project, I showcased my proficiency in data manipulation, visualization design, and dashboard creation using Power BI.
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HOUSE SALES DATA ANALYSIS - Perosnal Project - Excel and PowerBI
- In the real estate analytics, understanding housing market trends and patterns is crucial for both buyers and sellers. The “King County, Washington House Sales Analysis” is a comprehensive data visualization project that delves into the housing market. This project involved gathering, cleaning, and analyzing real estate data from Kaggle, followed by the creation of an interactive and insightful dashboard using Power BI.
-Project Phases:
- Data Collection: The project began by sourcing raw data from Kaggle, a popular platform for datasets. The dataset included a wealth of information about house sales. This data encompassed various features such as sale prices, location as latitude and longitued, number of bedrooms, bathrooms, and more.
- Data Cleaning and Preprocessing: Once the data was acquired, it required thorough cleaning and preprocessing to ensure accuracy and consistency. I used excel for tasks such as removing duplicates, handling missing values, and formatting data appropriately for analysis. This phase aimed to create a clean, organized dataset ready for further analysis.
- Dashboard Creation: The heart of the project was the creation of an interactive dashboard using Power BI, a powerful business analytics tool. Leveraging the cleaned dataset, I designed a user-friendly interface that allowed users to explore various facets of the housing market. The dashboard included visually engaging charts, line graph, map, and filters to provide an intuitive and dynamic user experience. Where in the bar charts, I try to create a histogram by using DAX formulas.
-Key Features of the Dashboard:
- Geospatial Visualization: A map visualization showcased the distribution of house sales across King County, helping users identify popular neighborhoods and areas of interest.
- Trends and Patterns: Time-series line charts demonstrated trends in house prices over the analyzed period, enabling users to understand fluctuations and seasonal patterns.
- Property Features Impact: Visualizations depicted how various features (e.g., bedrooms, bathrooms, square footage) influenced property prices, giving users insights into buyer preferences and market demand.
- Interactive Filters: Users could interact with filters to refine their analysis based on specific criteria such as year, month, day, year house bulit, square ft. living, and square ft. lot.
- Predictive Insights: Utilizing Power BI’s capabilities, I potentially integrated predictive models or trends to provide users with estimated future price trends or market forecasts.
-Project Impact:
- The King County, Washington House Sales Dashboard empowered users, including potential homebuyers, sellers, and real estate professionals, with data-driven insights. This interactive tool facilitated informed decision-making by shedding light on housing market trends, identifying investment opportunities, and understanding factors affecting property values. By presenting complex data in an accessible manner, This project contributed to enhancing transparency and efficiency in the housing market.
WORK EXPERIENCE
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TELUS INTERNATIONAL – Analyst – Remote
Research using online tools to determine and judge the intent and accuracy of queries. Applying market knowledge with provided guidelines to judge the relevance and intent of task information.
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FIVERR/UPWORK – Data Analyst and Visualization – Freelance
I offer expertly crafted, interactive dashboards using Power BI, Tableau, and Excel, tailored to your unique data needs. Data cleaning using Excel and SQL.
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ACCENTURE – Data Analytics and Visualization Virtual Internship
In this program By Accenture, I contributed to the project by conducting data cleaning, data modeling, and visualization I identified the most popular content categories through data-driven insights Through a PowerPoint presentation, I effectively communicated our analysis process showcasing knowledge in storytelling
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KPMG – Data Analytics Consulting Virtual Internship
I addressed data quality issues, strategized customer targeting, and crafted a detailed approach for analysis, including data exploration and modelling. I formulated a precise customer targeting strategy, outlined in a PowerPoint presentation I also designed a dashboard showcasing analysis results and proposed marketing strategies for growth Education
EDUCATION
BACHELOR OF ENGINEERING – SPPU – D.Y. Patil College of Engineering, Akurdi, Pune.
-CGPA: 8.39
LET’S CONNECT
- Mail : sanjeet.jagdale@gmail.com
- Phone : 9370132627
- LinkdIn