Enthusiastic Data Analyst with expertise in SQL, Power BI, and Microsoft Excel. Dedicated to ongoing personal growth.

Prachi Navlakhe  • Peerlist

Data Analytics professional at Schenider Electric having 2+ years of experience with Excel,SQL, Python,Tableau

The dataset includes the dish's name, diet type, course name, description, cuisine name, ratings, similar dishes, ingredients, preparation time, cooking time, total time, servings, and recipe instructions. This case study aims to clean and analyze the data to draw meaningful insights that can help improve data quality and support better decision-making. We have used SQL to clean the data.

Data Cleaning Practices Using SQL

Warehouse operations are the backbone of modern retail. I delved into an Amazon warehouse dataset to identify pain points and optimize processes. By leveraging advanced analytics and creating compelling visualizations with Power BI, I uncovered actionable insights that can revolutionize warehouse management.

FMCG Warehouse Analysis Using Power BI

Problem StatementProblem: Increasing customer complaints about late deliveries and product quality.Importance: Addressing these issues is crucial for improving customer satisfaction, retention, and ultimately, the company's revenue and reputation.Analyze DataCorp’s data to identify the root causes of customer complaints, particularly focusing on late deliveries and product quality issues. Provide actionable recommendations to address these problems.

NORTHWIND TRADERS ANALYSIS USING TABLEAU

I have created two interactive dashboards :Transaction Analysis: Provides insights into total interest, revenue trends (quarterly), and weekly growth. Credit Card Customers: Analyzes customer demographics by gender, offering insights into consumer behavior like age distribution and income patterns.

Credit Card Analysis Using Tableau

We have sales data from January 2023 to February 2024. We'll analyze sales achievements against individual targets, focusing on both year-to-date (YTD)performance and identifying the top performer for each month. This will help us understand overall progress towards goals, pinpoint areas for improvement, and recognize outstanding salesperson.

Sales Analysis Using SQL

"COFI PowerPlay: Analyzing Global Energy Investments" is an engaging and instructive case study designed for data science trainees. It delves into the complex world of global energy sector investments, focusing specifically on projects financed by Chinese entities under the Belt and Road Initiative (BRI). The study utilizes data from the China Overseas Finance Inventory (COFI) Database, which records diverse types of investments in power-generation projects across BRI countries.Problem Definition: Analyze the distribution of Chinese investments in renewable versus non-renewable energy projects in BRI countries to identify trends and suggest strategic investments for sustainable development.

COFI Power Play Using Looker Studio

<a target="_blank" rel="noopener noreferrer nofollow" class="text-green-text rich-link break-all link-break" href="https://public.tableau.com/views/EmployeeAttritionAnalysisDashboard_17155973178280/Dashboard1?:language=en-US&amp;:sid=&amp;:display_count=n&amp;:origin=viz_share_link">HR Analytics - Employee Attrition Dashboard</a>I used Tableau to create a comprehensive dashboard that provides insights&nbsp;into employee headcount, overall attrition rate, departmental breakdowns,&nbsp;and more. This data-driven approach allows us to make informed decisions about various HR initiatives.

Employee Attrition Analysis Using Tableau

Live Dashboard : <a target="_blank" rel="noopener noreferrer nofollow" class="text-green-text rich-link break-all link-break" href="https://public.tableau.com/views/EcommerceData_17150127608870/Dashboard1?:language=en-US&amp;publish=yes&amp;:sid=&amp;:display_count=n&amp;:origin=viz_share_link">Ecommerce Data | Tableau Public</a>This report analyzes data collected from our e-commerce store. The data encompasses details about customer demographics (city, country, etc.), their purchase history (order details like date, quantity, and total), and product information (including price, profit margin, and profit per order). This comprehensive data set allows us to gain valuable insights into customer behavior, product performance, and overall sales trends. By analyzing these aspects, we can identify areas for improvement, optimize marketing strategies, and make data-driven decisions to enhance our e-commerce operations.

Ecommerce Sales Data Using Tableau + SQL

<h3 class="rich-heading">Background:</h3>In this case study, will explore a dataset that captures unemployment rates across different countries from 1998 to 2022. The dataset provides an excellent opportunity to analyze global economic trends, understand regional disparities, and assess the impact of major global events on employment.Problem StatementAnalyze the global unemployment trends over three decades to identify patterns, anomalies, and the impact of major economic events (like the 2008 financial crisis and the 2020 COVID-19 pandemic).Why is it important to solve it?Understanding unemployment trends is crucial for policymakers, businesses, and international organizations to devise strategies for economic growth, workforce development, and crisis management.

Unemployment Trend Using SQL

Live Dashboard : <a target="_blank" rel="noopener noreferrer nofollow" class="text-green-text rich-link break-all link-break" href="https://app.powerbi.com/view?r=eyJrIjoiZWYxNDVlZTUtZTBjZS00MTBhLTg4ZDItNjUzYzBmMDY2NzNlIiwidCI6ImRmODY3OWNkLWE4MGUtNDVkOC05OWFjLWM4M2VkN2ZmOTVhMCJ9">https://app.powerbi.com/view?r=eyJrIjoiZWYxNDVlZTUtZTBjZS00MTBhLTg4ZDItNjUzYzBmMDY2NzNlIiwidCI6ImRmODY3OWNkLWE4MGUtNDVkOC05OWFjLWM4M2VkN2ZmOTVhMCJ9</a>The problem to focus on is identifying trends and inefficiencies in crop production across different regions and seasons, which is critical to making informed decisions that can lead to enhanced productivity and sustainability in agriculture.<h3 class="rich-heading">Data Dictionary</h3><ul><li>State: The state in which the crops are cultivated.</li><li>District: The specific district within the state.</li><li>Crop: The type of crop.</li><li>Crop_Year: The year of the crop data.</li><li>Season: The season in which the crop was cultivated.</li><li>Area: The area covered for the cultivation (in hectares).</li><li>Production: The total production obtained (in metric tonnes).</li><li>Yield: The yield of the crop per unit area (metric tonnes per hectare).</li></ul>

Crop Production Data Analysis Using Power BI

View the Dynamic Dashboard for a real-time overview<a target="_blank" rel="noopener noreferrer nofollow" class="text-green-text rich-link break-all link-break" href="https://app.powerbi.com/view?r=eyJrIjoiYTZkMWYzN2UtMTExMS00MWRhLTg2MTItMTdiNTljM2YwNzQ3IiwidCI6ImRmODY3OWNkLWE4MGUtNDVkOC05OWFjLWM4M2VkN2ZmOTVhMCJ9">https://app.powerbi.com/view?r=eyJrIjoiYTZkMWYzN2UtMTExMS00MWRhLTg2MTItMTdiNTljM2YwNzQ3IiwidCI6ImRmODY3OWNkLWE4MGUtNDVkOC05OWFjLWM4M2VkN2ZmOTVhMCJ9</a>PwC Switzerland Power BI Job Simulation on Forage - April 2024Completed a job simulation where I strengthened my Power BI skills to better understand clients and their data visualization needs. Leveraged analytical problem-solving skills to examine HR data, particularly focusing on gender-related KPIs, and identified root causes for gender balance issues at the executive management level, highlighting a commitment to data-driven decision-making.This dataset provides some insights:◾ The Promotion Rate .◾Turnover Rate.◾Hiring Rate , Age Level Impact om Job Level and more .

Diversity And Inclusion Analysis Using Power BI

View the Dynamic Dashboard for a real-time overview <a target="_blank" rel="noopener noreferrer nofollow" class="text-green-text rich-link break-all link-break" href="https://app.powerbi.com/view?r=eyJrIjoiM2IwMjg0ZDItNDIyMy00NDZiLWE5MDMtZjFiMWVhYTEwZGU5IiwidCI6ImRmODY3OWNkLWE4MGUtNDVkOC05OWFjLWM4M2VkN2ZmOTVhMCJ9">https://app.powerbi.com/view?r=eyJrIjoiM2IwMjg0ZDItNDIyMy00NDZiLWE5MDMtZjFiMWVhYTEwZGU5IiwidCI6ImRmODY3OWNkLWE4MGUtNDVkOC05OWFjLWM4M2VkN2ZmOTVhMCJ9</a>The challenge is to analyze the dataset to identify trends, preferences, and areas of improvement that can enhance the overall user experience on the platform. Specifically, the goal is to understand how different factors such as cuisine, location, price range, and ratings influence user choices and satisfaction.

Zomato Data Analysis Using Power BI

<h3 class="rich-heading">This interactive dashboard, built using Power BI, provides a comprehensive overview of call center's performance, leveraging data from PwC's&nbsp;job simulation program by forage. It empowers to easily visualize key metrics, identify trends, and gain valuable insights to optimize operations and improve customer experience.</h3>

CALL CENTER TREND ANALYSIS Using Power BI

The Auto Stock Data Analysis of Tata Motors, Hero Motors, Apollo Tyres, and TVS Motors project is an analysis of the historical stock data of these four Indian automobile companies. The project aims to identify trends in the stock prices, compare the performance of the different companies, and develop a trading strategy. I used python's library ( Pandas , Numpy , Matplotlib , Seaborn) for analysis and visualization to understand the data and the strategy for future predictions.

Link of the project : <a target="_blank" rel="noopener noreferrer nofollow" class="text-green-text rich-link break-all link-break" href="https://github.com/PrachiNavlakhe/Auto-Stocks-Data-Analysis">https://github.com/PrachiNavlakhe/Auto-Stocks-Data-Analysis</a>

Auto Stock Data Analysis Using Python

Analysis of mobile app data from the Play Store yields valuable insights. It reveals popular app categories, user preferences, and download trends. High-rated apps and positive reviews signify quality and user satisfaction. Pricing analysis helps determine optimal app pricing points. Geographical data identifies regional demands, aiding targeted localization. User engagement metrics showcase app stickiness. Identifying successful monetization strategies informs revenue generation. Uncovering reasons for app uninstalls improves user retention. Comparative analysis against competitors aids strategic positioning. Regular update frequency correlates with user engagement. Insights into user feedback inform app enhancements. Overall, Play Store data analysis empowers developers with actionable insights to optimize app features, marketing strategies, and overall performance, leading to increased downloads, user satisfaction, and business success.

Mobile Apps Play store Data Analysis Using Excel

Hotel booking data analysis offers valuable insights by examining booking trends, preferences, and customer feedback. Through rigorous data examination, it identifies peak booking periods, popular destinations, and preferred room types. This information guides revenue optimization strategies, resource allocation, and marketing campaigns. Moreover, the analysis unveils customer demographics, aiding in targeted promotions and personalized experiences. By studying booking cancellations and modifications, it improves operational efficiency and customer satisfaction. Patterns in booking sources highlight effective distribution channels. Sentiment analysis of reviews provides feedback for service enhancement. In essence, this data-driven approach empowers hotels to make informed decisions, enhance customer experiences, and maximize revenue potential.

Hotel Booking Data Analysis Using Excel

The project involves conducting a comprehensive data analysis of crimes against women in India. It aims to delve into crime statistics, patterns, and their underlying factors. By scrutinizing various forms of crimes such as harassment, violence, and discrimination, the project seeks to uncover trends and identify high-risk areas. The analysis will help generate insights that can guide policy-making, law enforcement strategies, and community interventions. By identifying vulnerable demographics and geographic regions, the project aims to propose targeted measures to enhance women's safety and rights. Ultimately, the goal is to contribute to a safer society by highlighting the challenges faced by women and suggesting evidence-based solutions for their protection and empowerment, fostering a more inclusive environment for all.

Crime Against Women in India Analysis Using Excel

A pizza sales analysis project involves a comprehensive examination of various aspects related to the sale of pizzas. It aims to extract valuable insights from sales data to inform strategic decisions. The project typically entails collecting and organizing sales data, including factors such as types of pizzas sold, pricing, time of day, customer demographics, and marketing initiatives. By applying statistical and data analysis techniques, patterns and trends emerge, revealing which pizza are most popular, which marketing strategies are effective, and when sales peak. These insights can guide menu optimizations, pricing adjustments, and targeted marketing campaigns. Moreover, the analysis might uncover correlations between certain variables and sales performance, aiding in making informed predictions and future plans. Ultimately, a pizza sales analysis project helps pizza businesses make data-driven decisions to enhance customer satisfaction, streamline operations, and boost profitability in a competitive market.