Project Details

This project analyzes and enhances Goodcabs' operations, targeting tier-2 cities across India, with a focus on improving service efficiency and expanding customer reach.

Key Focus Areas:

1. Boosting trip volumes in cities like Mysore, Coimbatore, and Vadodara.
2. Optimizing pricing strategies for high- and low-revenue cities.
3. Demand-based driver allocation to align with city dynamics.
4. Introducing Electric Vehicles (EVs) to reduce operational costs and appeal to eco-conscious passengers.
5. Collaborating with partners such as malls and hotels to expand the customer base.
6. Gathering more data for deeper insights into passenger and driver behavior.

Key Recommendations:

• Launch targeted campaigns and loyalty programs to increase trip volumes.
• Adjust pricing and service strategies based on city-specific trends.
• Optimize driver allocation by leveraging demand-based data insights.

Project video

Project Details

In this project, I used SQL to dive into the data and perform ad-hoc analysis, ensuring the information was accurate and relevant. I worked on extracting key insights from complex datasets, helping business owners make better, quicker decisions.

I turned to Python for data visualization to make the findings easier to understand. Using libraries like Matplotlib and Seaborn, I created clear and impactful visualizations, making the insights more accessible and actionable for everyone involved.

What I Learned:

• How to perform ad-hoc analysis and extract data using SQL.
• Creating engaging data visualizations with Python (Matplotlib, Seaborn).
• Streamlining data processes for better efficiency.
• Using visual storytelling to communicate insights more clearly.
• Presenting complex data in a way that simplifies decision-making.

Impact:
This project improved data analysis efficiency and empowered stakeholders to make informed, data-driven decisions with clarity.

Project video

Project Details

In this project, the goal is to create one report that could be used by stakeholders from sales, marketing, finance and executive team. The focus is made on the following,

1. Robust Data Modeling
2. User-empathetic Report design
3. Drillable Insights

I learned the following things in this project

1. Power Query (Basic and Advanced Operations)
2. Basic and complex DAX formulas
3. Data modelling involving 10+ tables
4. Choosing the right visuals and formatting
5. Dashboard designing principles
6. Using bookmarks
7. Deploying in Power BI service
8. Stakeholder Feedback Implementation
9. Sales, Marketing, Finance & Supply Chain metrics
10. Merging and Appending
11. Automatic data refresh using PBI service

Project video

Project Details

I utilized SQL queries to extract and analyze data, ensuring accuracy and relevance. I implemented stored procedures to streamline the process, automating repetitive tasks and enhancing efficiency. Additionally, I used views to improve query performance by simplifying complex data retrieval and ensuring faster execution. This combination of SQL techniques allowed for better data management and reporting.

I have learned the following:

1. Data retrieval using SQL queries.
2. Entity Relationship Diagram.
3. Extract, Transform, Load.
4. OLTP and OLAP.
5.SQL functions.
6. Creation of a Database.
7. SQL Data types.
8. Automation with stored procedures.
9. Streamlining data management
10. Kanban - Project Management Methodology.

Overall, this project aims to empower businesses with the necessary tools and insights to monitor, evaluate, and enhance their short-term goals. By leveraging data analysis, businesses can unlock new opportunities, drive growth, and stay competitive.

Project video