Welcome to my Tata Data Visualization project, which was completed as part of the Tata Group Virtual Internship on Forage. This Data Visualization Virtual Internship offered by Tata through Forage provides hands-on experience in leveraging data to create meaningful visual insights. By participating in this program, I had the opportunity to work on real-world data challenges faced by Tata Group’s businesses and enhance my skills in data visualization using Power BI.
The internship tasks were designed to simulate real-world business scenarios, requiring the use of data visualization techniques to solve complex problems and offer insights to business stakeholders.
- Project Overview
- Dataset Used
- Tools Used
- Background Information
- Task 1 - Framing the Business Scenario
- Task 2 - Creating Effective Visuals
- Findings
- Conclusion
This repository showcases my solutions to the tasks in the Tata Group Virtual Internship program. Each task is aimed at improving analytical decision-making using clean and interactive data visualizations.
The primary dataset used for this analysis can be found in the files uploaded to this repository.
- Excel: For ensuring accuracy and consistency in data for reliable analysis.
- Power BI: For designing interactive dashboards.
An online retail store has hired you as a consultant to review their data and provide insights that would be valuable to the CEO and CMO of the business. The business has been performing well and the management wants to analyse what the major contributing factors are to the revenue so they can strategically plan for next year.
The leadership is interested in viewing the metrics from both an operations and marketing perspective. Management also intends to expand the business and is interested in seeking guidance into areas that are performing well so they can keep a clear focus on what’s working. They would also like to view different metrics based on the demographic information that is available in the data.
A meeting with the CEO and CMO has been scheduled for next month and you need to draft the relevant analytics and insights that would help evaluate the current business performance and suggest metrics that would enable them to make the decision on expansion.
- As part of my role as a consultant for an online retail store, I was tasked with reviewing their data to provide key insights to help the CEO and CMO make strategic decisions for the coming year.
- The task is to develop relevant questions to prepare for an upcoming meeting with senior leaders, guiding the analysis and eventual presentation of key business metrics.
- Think from a business leader's perspective to analyze data more effectively.
- Prepare for a meeting with senior leadership by considering their key business concerns.
I was asked to draft four questions each for the CEO and the CMO to guide the development of insights. These questions must align with the unique perspectives of both leaders: the CEO focusing on overall business performance and expansion, and the CMO concentrating on marketing and customer demographics.
1. What are the major factors contributing to revenue?
2. How have our sales changed over the past year, and what do we expect for the next quarter?
3. How effective are our current marketing and sales strategies based on the dataset?
4. How has our overall business performance evolved month-over-month and year-over-year?
1. How is our company performing in each country?
2. What are seasonal trends in our data?
3. Which products are purchased by our customers, and what is the frequency of repeat purchases for these products?
4. What are the peak hours of the day during which our customers are most active and make purchases?
5. Which products are the top sellers in terms of quantity purchased, and what are the total sales figures for these products?
- For this task, the CEO and CMO of an online retail store have requested specific visualizations based on their business needs. These visuals will help in the strategic decision-making process, focusing on revenue trends, regional performance, and customer insights.
- I used Power BI for creating the visuals, ensuring that the data was clean and free of errors before analysis.
Before creating the visuals, I ensured the data was cleaned to eliminate errors such as negative quantities and incorrect unit prices. This was essential to ensure that the analysis reflects accurate and reliable insights.
1. Quality Check: Ensured that product quantities were not below 1 unit.
2. Unit Price Check: Verified that unit prices were not negative or below $0.
3. Applied conditional logic to filter out bad data, making the dataset fit for analysis.
After the data was prepared, I created the following visualizations using Power BI:
Description: The CEO of the retail store is interested to view the time series of the revenue data for the year 2011 only. He would like to view granular data by looking into revenue for each month. The CEO is interested in viewing the seasonal trends and wants to dig deeper into why these trends occur. This analysis will be helpful for the CEO to forecast for the next year.
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Purpose: To help the CEO understand monthly revenue fluctuations and identify peak periods.
Description: The CMO is interested in viewing the top 10 countries which are generating the highest revenue. Additionally, the CMO is also interested in viewing the quantity sold along with the revenue generated. The United Kingdom was excluded as per the request.
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Purpose: To analyze which countries drive the highest revenue and assess the quantity sold in those regions.
Description: The CMO of the online retail store wants to view the information on the top 10 customers by revenue. He is interested in a visual that shows the greatest revenue generating customer at the start and gradually declines to the lower revenue generating customers. The CMO wants to target the higher revenue generating customers and ensure that they remain satisfied with their products.
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Purpose: To help the CMO target high-revenue customers and ensure their satisfaction to foster continued business.
Description: The CEO is looking to gain insights on the demand for their products. He wants to look at all countries and see which regions have the greatest demand for their products. The data is presented in a single view to easily identify regions with high demand, aiding in the expansion strategy. There is no need to show data for the United Kingdom as the CEO is more interested in viewing the countries that have expansion opportunities.
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Purpose: To assist the CEO in identifying countries with the greatest demand for the company’s products.
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Purpose: The purpose of this visual is to understand order distribution trends throughout the day. We can identify high-traffic hours, peak hours. Additionally, it provides insights into customer behavior as well.
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Monthly Revenue for 2011
- Seasonal Peaks: We saw significant revenue peaks in March, May, and November.
- Highest Revenue: November stands out with highest revenue reaching approximately $1.20 millions.
- Year-End Drop: Ther is a noticeable drop in December.
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Top 10 Countries by Revenue and Quantity Sold
- Countries like Germany and France show higher total revenue compared to quantity sold, indicating there might be purchasing higher-priced products.
- Netherlands leads the pack in both revenue and quantity sold.
- Countries like Japan and Sweden aren't performing well, which might present opportunities for growth.
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Global Product Demand by Country
- North America and parts of Europe stand out with high demands, as indicated by larger circles.
- Regions like Africa and South America show samller circles, suggesting potential growth opportunities.
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Total Orders over Time
- Highest number of orders are around midday i.e. between 12PM to 2PM.
- The number of orders fluctuates throughout the day.
This project demonstrates not only my technical skills in data visualization but also my commitment to delivering high-quality, actionable insights.