Project Details

In this project, the primary objective is to craft a unified report catering to stakeholders in sales, marketing, finance, and the executive team. The key focus areas are:

1. Robust Data Modeling
2. User-centric Report Design
3. Drillable Insights

Throughout this project, I acquired proficiency in various aspects:

1. Power Query: Executing both basic and advanced operations.
2. DAX Formulas: Mastery in crafting basic and complex formulas.
3. Data Modeling: Handling intricate structures involving over 10 tables.
4. Visual Selection: Choosing appropriate visuals and mastering formatting.
5. Dashboard Design: Applying principles for effective dashboard creation.
6. Bookmarks: Utilizing bookmarks for enhanced user experience.
7. Deployment: Successfully deploying the project in Power BI service.
8. Feedback Implementation: Incorporating stakeholder feedback.
9. Metrics Mastery: Gaining insights into metrics spanning sales, marketing, finance and supply chain domains.

Live Interactive Dashboard

Project Details

Problem Statement :
Atliq Grands owns multiple five-star hotels across India. They have been in the hospitality industry for the past 20 years. Due to strategic moves from other competitors and ineffective decision-making in management, Atliq Grands are losing its market share and revenue in the luxury/business hotels category. As a strategic move, the managing director of Atliq Grands wanted to incorporate “Business and Data Intelligence” in order to regain their market share and revenue. However, they do not have an in-house data analytics team to provide them with these insights.

Data-Driven Results :
1. Enhanced a Power BI dashboard by leveraging a 3-month dataset for AtliQ Grands, resulting in a 5% increase in market share and a 3% uptick in revenue during the subsequent quarter.
2. Leveraged dashboard insights, the Revenue team at AtliQ Grands aims for a 10% recovery in both revenue and market share in the next month.

Live Interactive Dashboard

Project Details

The objective of this predict the ordinal variable damage_grade, which represents a level of damage to the building that was hit by the earthquake. There are 3 grades of the damage:

1 represents low damage.
2 represents a medium amount of damage.
3 represents almost complete destruction.

The dataset mainly consists of information on the buildings' structure and their legal ownership. Each row in the dataset represents a specific building in the region that was hit by Gorkha earthquake. There are 39 columns in this dataset, where the building_id column is a unique and random identifier.

To measure the performance of our algorithms, we'll use the F1 score which balances the precision and recall of a classifier.

This project helped me gain insights on :-
1. Python programming
2. Exploratory Data Analysis
3. Python libraries
4. Machine Learning Models

Project Details

Project Description:
Establishing an innovative reporting mechanism, this project aims to assist businesses in evaluating customer discounts, engaging in effective negotiations, and identifying lucrative expansion opportunities. The generated reports are designed to provide actionable insights, optimizing sales strategies, enhancing customer satisfaction, and ultimately maximizing revenue. The sales analytics system implemented in this project allows for real-time tracking of performance against targets, pinpointing areas for improvement, and aligning sales efforts with overarching business goals.

Learnings: -
1. Insightful analysis of generated reports to refine sales strategies.
2. Real-time performance tracking against predefined targets.
3. Identification of areas for improvement within sales processes.
4. Alignment of sales efforts with broader business objectives.
5. Utilization of comprehensive tools for continuous monitoring and evaluation of sales activities.