Portfolio - Sheethal V

PowerBI Project

Business Insight 360

Domain/Function: Brick & Mortar and E-Commerce

Developed a Power BI dashboard for AtliQ Hardware, processing 1.8M+ records from SQL and Excel/CSV to uncover key business trends. Built data models, optimized reports with DAX Studio, and enhanced performance by 5%. Enabled data-driven decisions, driving a 10% revenue boost and 20% cost savings.

Other Tools

Power BI | MySQL | Excel | Dax Studio

Integrating a user-friendly and intuitive landing page within the dashboard to enhance user experience and accessibility.

Executive view: Offers historical data on crucial metrics & KPIs for executive members. enabling strategic decision making.

Project Details

Problem: AtliQ struggled with inefficiencies and financial losses due to Excel-based data analysis.

Objective: Transition to Power BI for real-time insights and better decision-making.

Key Features

-Finance View: Analyzes P&L., revenue, and profitability.

-Sales View: Tracks Net Sales, Gross Margin, and growth.

-Marketing View: Evaluates product performance.

-Supply Chain View: Monitors forecast accuracy and risks

-Executive View: Provides an overall business snapshot

Implementation

-Data modeling with 15 tables- Used Snowflake schema.
-DAX measures
-calculated columns
-Bookmarks
-page navigation
-Dynamic titles
- conditional formatting
-Visualization: Created interactive dashboards

Automation Power BI Gateway enabled real-time updates

Conclusion: Enhanced AtliQ's efficiency, analytics, and decision-making.

Excel Project

P & L Report

Domain/Function: Sales and Finance

Created 2 reports for the sales team which will help them to evaluate customer performance and understand their market performance with respect the their target

This visual shows the net sales performance of various customers for AtliQ Hardware from 2019 to 2021, highlighting the percentage growth.

This visual shows the Market performance VS Target of various customers for AtliQ Hardware from 2019 to 2021, highlighting the percentage growth.

Project Details

The goal of this project was to provide the sales and finance teams with key insights into their business performance. By analyzing sales data, the project aimed to identify trends, improve decision-making, and support strategic planning.

Sales View: The reports created for the sales team focused on metrics such as net sales, customer segmentation, and product performance. This helped the team to better understand their market and optimize their sales strategies.

Finance View For the finance team, the reports provided insights into financial metrics like revenue, gross margin, and profitability. These insights were crucial for budgeting. forecasting, and ensuring financial health.

During this project. I honed my skills in Excel, specifically in using Power Query for data transformation and DAX basics for calculations. Additionally, I leveraged Power Pivot to create complex data models, enabling the generation of detailed and insightful reports.

SQL Project

Movie Database Analysis Using SQL

Domain/Function: Entertainment / Movie Industry

This project involves analyzing a movie database using SQL. It includes queries to extract insights such as movies from specific studios, industry-specific trends, and details about popular franchises like Marvel and Bollywood. The project showcases SQL skills in data retrieval and filtering.

A CTE is used to filter Hollywood movies released after 2000 with a profit above 500 million by computing revenue minus budget efficiently.

This query retrieves Hindi movies sorted by revenue in millions using JOINs between movies, financials, and language tables for analysis.

Project Details

The Movie Database Analysis Using SQL project extracts insights from a structured movie dataset using advanced SQL techniques. It involves querying and analyzing movie data to explore industry trends, production studios, and franchises.

Key objectives include:

Retrieving movie titles and release years based on studios (e.g., Marvel Studios).
Searching for movies with specific keywords (e.g., "Avengers").
Identifying distinct studios in various industries, like Bollywood.
Filtering movies by genres, release years, and attributes.
Applying JOINs to merge multiple tables for deeper insights.
Using CTEs to simplify complex queries and enhance readability.
Implementing subqueries for filtering and extracting specific insights.
Utilizing aggregate functions and data manipulation for trend analysis.
This project highlights SQL expertise in data retrieval, filtering, aggregation, JOINs, CTEs, and subqueries, benefiting entertainment data analysts and business intelligence.

Excel Project

BlinkIT Grocery Sales Analysis

Domain/Function: Retail / Grocery Sales Analysis

This project analyzes grocery sales data from BlinkIT, focusing on product categories, outlet performance, and key sales trends. It provides insights into factors affecting sales, outlet types, and customer preferences using Excel-based dashboards and data visualization techniques.

The BlinkIT Grocery Sales Analysis project aims to explore sales trends across different product categories, outlet types, and locations. The dataset

An interactive sales analysis dashboard displaying item sales by fat content, outlet size, location, and establishment year, with dynamic filters.

Project Details

The BlinkIT Grocery Sales Analysis project aims to explore sales trends across different product categories, outlet types, and locations. The dataset includes attributes such as item type, fat content, outlet establishment year, outlet size, location type, item visibility, and total sales. The analysis involves data cleaning, exploratory data analysis (EDA), and visualization using Excel and Python. A dynamic Excel dashboard is created to provide insights into top-selling items, outlet performance, and rating trends, enabling data-driven decision-making for retail business improvements.

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Sheethal V

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Business Insight 360

P & L Report

Movie Database Analysis Using SQL

BlinkIT Grocery Sales Analysis

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Sheethal V

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