Naredlla Sandeep Reddy

Blinkit Analysis Project Using Power BI! 📊 I’m thrilled to present my latest project, where I analyzed Blinkit’s sales data using Power BI. This analysis involved a comprehensive examination of various factors influencing sales performance. Here’s a snapshot of what I explored: 1️⃣ Item Fat Content & Weight: Analyzed the impact of item fat content and weight on sales to understand customer preferences for healthier or heavier products. 2️⃣ Item Identifier & Type: Investigated the performance of different item types to identify top-selling products and categories. 3️⃣ Outlet Characteristics: Evaluated sales performance across various outlet types, locations, and sizes to optimize store operations and placement strategies. 4️⃣ Outlet Establishment Year: Analyzed the influence of outlet age on sales to determine how establishment year correlates with sales performance. 5️⃣ Sales Trends: Explored item visibility and sales data to identify trends and make data-driven recommendations for improving sales strategies. 6️⃣ Rating Analysis: Examined customer ratings and their impact on sales to gauge product popularity and customer satisfaction. Using Power BI, I created dynamic and interactive dashboards to visualize these insights, enabling better decision-making and strategic planning. A big thank you to Rishabh Mishra Hrithik Mehlawat Harman Singh Murrad On Run for the support and resources provided during this project! 🔍 Check it out here: bit.ly/4cLNvkd 🔍 Business requirements: bit.ly/3yF6P4x #DataAnalysis #PowerBI #Blinkit #SalesPerformance #BusinessIntelligence #DataVisualization #CustomerInsights

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The primary goal of a dashboard is to provide actionable insights to stakeholders. What do I mean by that? Take this dashboard made in Tableau below, it shows all my cycle rides which I have recorded in Strava app. In what ways it is useful for me? 1. I can see my overall progress since 2021 when i took up cycling as a daily habit. 2. I can see how active I am over the past 7 days by measuring the distance covered 3. Most importantly to motivate myself to achieve the target I have set for myself, currently i have set for 600 rides. So if you see overall if you want to understand analytics you can start by looking into your own data and make interpretations out of it. Let me know your thoughts on this. #tableau #datavisualization

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🚀 Exciting News! 🚀 I'm thrilled to announce that I've successfully completed an Introduction to Power BI course! 💡 As a Business Analyst, mastering tools like Power BI is essential for driving data-driven strategies and making informed decisions. Throughout this immersive course, I've deepened my understanding of Power BI's capabilities and honed my skills in leveraging data visualization to drive business insights. 💼 🌟 What I've Gained: - Proficiency in creating interactive dashboards and reports using Power BI, enabling me to visualize complex data sets effectively. - Skills in connecting and transforming data from various sources, ensuring data integrity and accuracy in analysis. - Knowledge of data modeling and visualization best practices, allowing me to communicate insights clearly and persuasively to stakeholders. - Experience in sharing insights and collaborating with teams, fostering a culture of data-driven decision-making within organizations. I'm excited to apply my enhanced expertise in Power BI to drive business growth, optimize processes, and unlock new opportunities for success. 🔍 Let's connect and explore how I can leverage Power BI to drive impactful outcomes for your organization! 📊 #PowerBI #BusinessAnalysis #DataVisualization #BusinessIntelligence #ProfessionalDevelopment #LinkedInLearning

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Data driven problem solving is a must have skill in today's era when every company aspires to be a Data + AI company. Every business function requires reporting and compliance that requires a lot of data crunching. Industries that are highly data driven (ex. Retail, CPG, Insurance etc.) are getting fast transformed due to arrival of data driven apps (read SaaS) that are bringing high efficiency and hence customer satisfaction. Hence, the need for teams that understand and have experience with leveraging data to solve business problems is ever growing. With GenAI accelerating analytical workflows, the data team at workplace doesn't look siloed anymore. Every team member be it a Data Analyst, Data Engineer, Data Scientist has to roll up to their sleeves and develop deeper understanding of the domain and leverage data to solve the same using technology. In short, data teams would need to upgrade to having : Domain Knowledge+ Data skills + Technology skills held strongly together for solving business problems faster and better. We at Enqurious (formerly Mentorskool) are bringing together our collective experience of upskilling 3000+ data engineers in the past 4 years and building a place to engage, enquire, experiment, explore and experience data driven problem solving. Here's a short, curated skill path in Snowflake that you can try : https://lnkd.in/gEhMVrNn This and lot more happening at #EnquriousAcademy #learningexperience #datadriven #problemsolving #domain #data #dataengineering #ml

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FREE DEMO CLASS Comment down if you also want to get get free demo class on Data Science and Data Analytics Learn From the industry expert

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The Govt asks QCommerce firms to prove their claim of delivering within 10 minutes. Imagine you are a Data Analyst working as part of Blinkit's data team. How would you approach this problem? What questions would you ask your data? What is the right metric to work with? What concepts would be required to attempt this problem? Welcome to the world of Descriptive and Inferential Statistics with Hypothesis testing being the key to the lock. Remember? When p is low, null should go! Discover another such scenarios across industry domains like E-commerce and Insurance : https://lnkd.in/dkjASWqS Whether you are in individual data professional or are leading high performing data teams, getting good grasp on the essentials of Statistical Thinking is critical to enable them solve real world problems like this. Discover our 4D framework of upskilling and learn more about our offerings at our stall at #DES2024 #descriptivestats #inferentialstats #experientiallearning #dataanalytics #statistics

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📈 Data-Driven Decisions with Blinkit Power BI Dashboard. This Power BI dashboard provides a comprehensive overview of Blinkit performance metrics, offering actionable insights for smarter business decisions. 1. Total Sales Overview $1.20M in total sales, with 8,523 items sold. Insight: High sales volume indicates strong customer demand. Monitoring the top-selling categories can help sustain growth. 2. Fat Content Analysis Regular products: $776.32K (65% of sales). Low-fat products: $425.36K (35% of sales). Insight: Regular products dominate sales. However, increasing the visibility of low-fat items could target health-conscious customers and expand market share. 3. Item Type Performance(Top Categories by Sales): Fruits & Vegetables: $0.18M. Snack Foods: $0.18M. Household: $0.14M. Frozen Foods: $0.12M. Insight: These categories generate the most revenue, highlighting the need for maintaining inventory and competitive pricing in these segments. 4. Outlet Performance by Tier Tier 3: $472.13K (highest sales). Tier 2: $393.15K. Tier 1: $336.40K. Insight: Tier 3 outlets are leading in sales, showcasing strong demand in less urbanized regions. These outlets could be prioritized for expansion or promotions. 5. Outlet Size Contribution Medium-sized outlets: $507.9K (42.3% of total sales). Small outlets: $444.79K. Large outlets: $248.99K. Insight: Medium-sized outlets generate the highest sales, likely due to optimized product variety and manageable operational costs. 6. Outlet Establishment Trends (Over Time) Sales peaked at $0.20M during a specific period (likely due to promotions or seasonal demand). Insight: Seasonal or event-based promotions could be explored further to replicate such high-performance periods. 7. Outlet Type Breakdown by Sales Supermarket Type 1: $0.79M (most profitable). Supermarket Types 2 & 3: $0.13M each. Grocery Store: $0.15M. Insight: Supermarket Type 1 is the clear leader, suggesting a superior product mix or customer preference for this format. 8. Customer Feedback - Average Ratings Average customer rating is 3.9. Insight: While the rating is relatively steady, efforts to push it above 4.0 could enhance customer loyalty and trust. Actionable Recommendations: -Focus on Tier 3 Outlets: Invest in inventory and marketing strategies to leverage the high demand. -Enhance Customer Experience: Focus on boosting ratings above 4.0 by addressing common pain points. -Promote Low-Fat Items: Expand product visibility for low-fat items to cater to a growing health-conscious audience. -Leverage Insights from Medium-Sized Outlets: Replicate the model of these outlets in other locations. -Seasonal Campaigns: Analyze peak sales periods and replicate success through targeted promotions. 📊 Data visualization enables businesses to spot opportunities, streamline operations, and deliver better experiences! #DataAnalysis #RetailInsights #PowerBI #Blinkit Blinkit #MySQL #AdavancedExcel #PowerBI Club Let me know if you’d like to tweak this further!

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Hello everyone, I am participating in FP20 Analytics Challenge 20 - Email Campaign Performance analysis. The dashboard is designed to analyze campaign performance across client segments, devices, countries. Here's the link to the Dashboard: https://lnkd.in/ddh8-tKF Key insights: 1. Overall Trends - Emails Sent & Open Rate increased steadily from July to September. - Click-Through Rate (CTR) & Conversion Rate improved from July to August but dropped in September. - Unsubscribed Rate has Noticeable increase from August to September, requiring attention. 2. Campaign Performance by Type - Events & Webinars account for nearly 70% of all campaigns. - Newsletters have the highest number of emails sent but Promotional Campaigns show the best performance, with the highest conversion rate and the lowest unsubscribe rate. - Discount Offers for Influencers lead the charts with both the highest CTR and conversion rate, suggesting high engagement among this segment. 3. Performance by Day - Sundays have the highest average CTR and conversion rate, indicating better engagement on weekends. 4. Client Segments - Lead Segment Clients engage more through clicks, showing higher CTR than other segments. - Customer Segment Clients show higher open rates, but both segments have similar conversion rates. 5. Device Usage & Email Engagement - Desktop and Mobile Devices are the dominant platforms for opening emails. - Desktop Users have higher conversion rate compared to mobile users. - Tablet has 100% CTR, but only one mail opened, so results aren’t statistically meaningful. 6. Domain and Bounce Rates - AOL Domain has Highest bounce rate among all domains, indicating possible delivery issues. 7. Geographical Insights - India has the largest client base, but open rate, CTR, and conversion rates are below expectations. - Iceland, Vanuatu, Guinea show high conversion rates, but their small client base limits overall impact. - Countries like Syria, Laos, Luxembourg report 0% CTR and conversion rate, suggesting missed engagement opportunities. - Top Client Countries (India, US, Brazil) have conversion rates are below 5%, signaling the need for targeted optimization. Thank you Federico Pastor, ZoomCharts for this opportunity. #FP20Analytics, #FP20EmailCampaignPerfromanceAnalysis, #builtwithzoomcharts #powerbi #datavisualisation

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Starting the next batch on Data Engineering from 17th July 2024. You will learn Data Management, Data Analysis, Data Processing, Data Warehousing, how data is stored in Cloud in different formats and Data Visualization techniques using Excel and PowerBI is what we cover. If you or any of your team or any of your friends or relatives looking for a solid foundational knowledge on DATA and its usage across Enterprises, please ask them to enroll into the program. Reach out to operations team to get enrolled into this program. We can customize / personalize the content for your needs. #dataengineering #datawarehouse #SQL #excel #PowerBI #Pandas #Python #AWS #DataTraining

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Analyzing Global Impact: Estimating the Economic Contribution of Hero motoCorp's Using Data Analytics. To analyze Hero MotoCorp's global sales using Tableau, you would typically follow these steps: Collect Data: Obtain sales data from Hero MotoCorp. This might include sales figures by region, country, or model, as well as time periods. Prepare Data: Ensure your data is clean and structured properly. This might involve formatting dates, categorizing regions, and ensuring numerical values are consistent. Load Data into Tableau: Import your prepared data into Tableau. You can do this by connecting to your data source (Excel, SQL database, etc.). Build Visualizations: Maps: Create geographical maps to visualize sales by region or country. Tableau’s mapping capabilities can help illustrate where sales are strong or weak. Time Series Analysis: Use line charts or area charts to track sales over time, which can help identify trends or seasonal patterns. I would like to extend my heartfelt thanks to Dr James Daniel Paul P Sir for their invaluable guidance.

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Just mastered Power BI with Aditi Mam —transformed raw sales data into actionable insights. Now making data-driven decisions, enhancing production, and shaping the future. Grateful for the guidance! key insights: 1. Overall Performance:   - Total sales: $2.64M   - Profit: $1.47M   - Quantity sold: 178K units   - Shipping cost: $1.35M 2. Sales by Category:   - Technology appears to be the top-selling category, followed closely by Furniture and Office Supplies. 3. Market Distribution:   - APAC seems to be the largest market, occupying a significant portion of the pie chart.   - Other major markets include US, EMEA, and LATAM. 4. Shipping Modes:   - Standard Class is the most used shipping mode (7.51M), followed by Second Class (2.57M) and First Class (1.6M).   - Same Day shipping is used least frequently. 5. Geographic Focus:   - The dashboard includes data for Africa, APAC, and Canada, suggesting a global presence. 6. State-wise Sales:   - There's a chart showing sales by state, but the details are not clearly visible in this image. 7. Profit Margin:   - With sales of $2.64M and profit of $1.47M, the profit margin appears to be quite healthy at about 55.7%. 8. Shipping Cost Impact:   - Shipping costs ($1.35M) are significant, accounting for about 51% of total sales, which could be an area to optimize. 💡💪 #PowerBI #DataDrivenDecisions TechTip24 Aditi Gupta

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Love a challenge and have a curious mind? Data Science explores hidden insights across industries. Become a Data Master and launch your dream career. Enroll Now! #bseinstitute #bseindia #datascience #machinelearning #datavisualization #dataanalytics #machinelearning #data #vocationalprogram #reel #reelsindia #educationreel

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Month 2 Day 2: Power BI Upskilling and Interview Preparation max and min in the line chart from Shashank Singh 🇮🇳 YouTube channel Practiced using Power BI with a sales table as part of my ongoing upskilling. Created a line chart by dragging and dropping the sales and products fields. Developed a measure to calculate total sales. Two additional measures were created using the IF, MAXX, and MINX functions. Removed the original sales data from the line chart and added the total sales, maximum value, and minimum value measures. Applied formatting to highlight different colors for the measures, which worked perfectly. Practiced six questions and implemented them using data in Power BI. better reach Continuous learning and practice are key! 💪 for better reach: Shashank Singh 🇮🇳 Raghavan P Munna Das MADHU THANGELLA Gaurav Agrawal Ankit Bansal #PowerBI #DataAnalytics #LearningJourney #InterviewPreparation

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Hi Connections, This is my first hashtag #project in Tableau. Project Name: IPL ANALYSIS 2008-2020 The Indian Premier League (IPL) is a professional Twenty20 cricket league in India, played annually by franchise teams representing different cities in India. The league was established in 2008 and has since become one of the most popular sports events in the country, attracting millions of fans from all over the world. The data to make this project I have taken from kaggle. In this project, I have visualized the data in a way to help the cricket association to hashtag #analyze the data in a meaningful way so, I designed a full hashtag #report in an interactive way and I worked in all these hashtag #kpi 's like 1️⃣ IPL Winner Season wise. 2️⃣ Orange cap holder( Maximum no. of runs which batsman has made season wise). 3️⃣ Purple cap holder( Maximum wickets a baller has taken in a particular season). 4️⃣ Matches won as per the toss. 5️⃣ Percent of winning as per the toss decision. 6️⃣ No. of 4 runs per season. 7️⃣ No. of 6 runs per season. 8️⃣ Teams and Batsman total runs 🔸 While working with the above KPI's, I have learned ; ⚪ Implementing data blending and aggregation ⚪ Working with its dashboard ⚪ To calculate field through analysis. ⚪ To build a dual axis pie chart. Under the guidance of Akash Raj and CloudyML Team members. Overall, Tableau can be a powerful tool for analyzing and visualizing IPL data, helping us uncover insights and trends that can inform our understanding of this exciting and popular sports event. hashtag #dataanalysis hashtag #dataanalytics hashtag #dataanalyst hashtag #datascience hashtag #dataanalystjobs hashtag #tableaupublic hashtag #tableau hashtag #tableaudashboard hashtag #datasciencejobs

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Develop an interactive Power BI dashboard to monitor online sales across different regions in India. Highlight key insights such as the highest market state, most profitable product category, top 5 customers by name, most used payment mode, and monthly profit trends. Enable data-driven decision-making and strategic planning for the store owner. 𝐃𝐚𝐭𝐚 𝐈𝐦𝐩𝐨𝐫𝐭𝐢𝐧𝐠 (𝐂𝐒𝐕): Imported sales data from CSV files into Power BI for comprehensive analysis. Ensured data quality and consistency by cleaning and transforming the imported data. 𝐃𝐀𝐗 𝐐𝐮𝐞𝐫𝐲 𝐟𝐨𝐫 𝐀𝐎𝐕: Used DAX Query for Calculating AOV (Average Order Value): Implemented the formula `AOV = [Total Sales] / [Number of Orders]` to measure the average value of each order placed. 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬: 𝐒𝐭𝐚𝐜𝐤𝐞𝐝 𝐁𝐚𝐫 𝐂𝐡𝐚𝐫𝐭: Displayed the sum of amount by states and sum of profit by sub-category, providing a clear comparison of sales and profitability across different regions and product categories. 𝐃𝐨𝐧𝐮𝐭 𝐂𝐡𝐚𝐫𝐭: Illustrated the sum of quantity by category, showing the distribution of sales volume across different product categories. 𝐒𝐭𝐚𝐜𝐤𝐞𝐝 𝐂𝐨𝐥𝐮𝐦𝐧 𝐂𝐡𝐚𝐫𝐭: Showed profit by month and sum of amount by customer name, highlighting monthly profitability trends and identifying top customers by sales amount. 𝐂𝐚𝐫𝐝: Highlighted key metrics such as total sales, total profit, and average order value, Sum of quantity sold.

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Visualizing Titan’s Presence Across India! Excited to share a Tableau map I created, showcasing the number of Titan Co. Ltd. outlets in each state across India. This visualization highlights the company’s widespread reach and offers a clear perspective on its regional presence. It’s amazing how tools like Tableau make data so accessible and easy to interpret. Looking forward to diving deeper into more data visualization projects! #Tableau #DataVisualization #TitanCo #BusinessInsights #LearningJourney

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Recently, I had the chance to explore 𝐀𝐥𝐭𝐞𝐫𝐲𝐱, 𝐐𝐥𝐢𝐤𝐒𝐞𝐧𝐬𝐞, 𝐚𝐧𝐝 𝐐𝐥𝐢𝐤𝐕𝐢𝐞𝐰 —three tools that are becoming increasingly relevant in a data analyst or a business analyst role. Here are some key takeaways from my deep dive : 1️⃣ 𝐀𝐥𝐭𝐞𝐫𝐲𝐱 : I found it incredibly intuitive for data preparation and blending. What stood out to me is how it empowers users to automate complex workflows without needing to write code. It’s a huge time-saver for anyone who needs to handle large datasets or repetitive tasks. 2️⃣ 𝐐𝐥𝐢𝐤𝐒𝐞𝐧𝐬𝐞 : The self-service capabilities are impressive. The ability to explore data interactively, without predefined paths, allows for a deeper understanding of trends and outliers. It’s perfect for teams that want to make data-driven decisions on the fly, with minimal technical barriers. 3️⃣ 𝐐𝐥𝐢𝐤𝐕𝐢𝐞𝐰 : While QlikView might be older, its guided analytics approach is still highly valuable. It’s especially useful for structured, repeatable analyses where the goal is to ensure users follow a consistent path through the data. I can see why it’s still favored in environments where control and consistency are key. These tools have opened my eyes to new ways of working with data and have given me fresh ideas on how to leverage them in real-world projects. Excited to continue learning and applying these insights! #sql #mysql #businessanalyst #dataanalytics #dailycoding #databasemanagement #dataanalyst 

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In the IPL, an analysis of the top batters can categorize them based on their impact as follows: 🏏 - Very Impactful Batters - Partially Impactful Batters - Less Impact Batters - Blind Sloggers #IPL | #IPL2024 | #IPLT20 | #IPLCriket Give a look to this 1 minute read article. ⬇ https://lnkd.in/dK8UxzQe

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