Project Details

Conducted a detailed analysis of BrowserStack's churn data, segmented by region, establishment type (individual developer vs. company), and seat utilization. Applied statistical techniques to identify patterns and provided insights to inform future actions

Questions Answered in the assignment -
1) Based on the data above, the churn in BrowserStack is 29.9%. But this is of limited use. Can you calculate churn in a way that provides better insight? What is that insight?
2) What are the top 3 parameters that may be causing churn from the above dataset and explain why? For each of these parameters, what are potential things we can do to address churn?
3) What is your inference about repurchases using this dataset?

Project Details

Project Overview:
The project unfolds in three pivotal stages:

🧹 Data Cleaning:
Rectified negative values in the Number of Guests. Eliminated outliers in Revenue Generated & Realized. Addressed NaN/Null values in Ratings Given.

🔄 Data Transformation:
Introduced the concept of 'Occupancy Percentage' derived from successful bookings and capacity. Explored nuanced insights based on the transformed dataset.

Project Details

This project presents data insights of P&G Asia.
Dashboard contains-
1) YoY regional sales
2) YoY SKU sales
3) SKU Sales based on individual regions

Project Details

AtliQ Mart is a growing FMCG manufacturer headquartered in Gujarat, India. It is currently operational in three cities Surat, Ahmedabad, and Vadodara. They want to expand to other metros/Tier 1 cities in the next 2 years.

AtliQ Mart is currently facing a problem where a few key customers did not extend their annual contracts due to service issues. It is speculated that some of the essential products were either not delivered on time or not delivered in full over a continued period, which could have resulted in bad customer service. Management wants to fix this issue before expanding to other cities and requested their supply chain analytics team to track the ’On time’ and ‘In Full’ delivery service level for all the customers daily basis so that they can respond swiftly to these issues.

Live Interactive Dashboard

Project Details

Atliq Hardware is a leading company in the computer hardware industry, renowned for its innovative products and extensive market reach in India and internationally.

Challenge Description

The challenge involved solving 10 ad-hoc business queries to improve Atliq Hardware's analytics capabilities. Using SQL, the objective was to extract insights from the provided dataset and present these findings effectively to aid management in making informed decisions.

Tools and Technologies

MySQL: Crafting precise SQL queries and performing data analysis.
Microsoft Power BI: Creating compelling presentations of the insights.

Conclusion

This project was an enriching experience that enhanced my SQL skills and provided deep insights into business analytics. The outcomes hold significant potential for driving impactful business strategies at Atliq Hardware.

Project Details

Project Details

● Armed with a sample dataset featuring 4000 customers across five cities, my role as a data analyst unfolded. The primary objective is to analyze this dataset to unveil key insights that would guide the product strategy team in tailoring the credit cards to customer needs and market trends.
● The heart of the project involved designing a Power BI dashboard—an intuitive visual tool aimed at top-level management and the product strategy team. The success of this venture pivoted on the dashboard's self-explanatory nature and its ability to convey complex insights with simplicity.
● In one of the insights, I found that the overall average monthly credit card spending is highest in Bills, followed by Electronics, and Health and wellness categories.
● Also, the overall average monthly credit card spending is highest in the 25-34 age group with 15.3 Million ₹, followed by the 35-45 age group with 11.9 Million ₹

Live Interactive Dashboard