Aashish Vidhudi | Business Analyst & AI Portfolio

About Me

I am a results-driven Business Analyst with strong expertise in data analysis, stakeholder management, and AI-powered insights. I specialize in transforming business requirements into scalable, technology-driven solutions.

My focus is on improving operational efficiency, enabling data-driven strategies, and leveraging Artificial Intelligence for smarter business decisions.

Core Skills

Business Requirements Analysis Stakeholder Management Process Mapping (BPMN) Agile & Scrum SQL Advanced Excel Power BI Tableau JIRA & Confluence UML Diagrams Risk Analysis Documentation (BRD/FRD)

AI & Analytics Expertise

AI-Powered Analysis

Prompt Engineering for Business Use
AI-Assisted Market Research
Automated Reporting
Decision Support Systems

Machine Learning Basics

Regression & Classification Models
Predictive Analytics
Customer Segmentation
Forecasting Models

Data & Visualization

Python (Pandas, NumPy)
Power BI Dashboards
Data Storytelling
Interactive Reports

Featured Projects

AI-Based Sales Forecasting System

Developed a predictive analytics solution using historical sales data and machine learning models to improve revenue forecasting accuracy.

Improved forecast accuracy by 22%
Reduced inventory waste
Enabled executive dashboards

Customer Experience Optimization

Led business analysis for a digital transformation initiative focused on improving customer journey and retention.

Mapped end-to-end processes
Implemented AI chat analysis
Increased retention by 18%

Operational Efficiency Dashboard

Designed Power BI dashboards for monitoring KPIs across departments.

Automated reporting
Reduced manual work by 40%
Improved leadership visibility

Professional Approach

Requirement Elicitation through Workshops & Interviews
Gap Analysis & Root Cause Analysis
Solution Validation & UAT Support
Continuous Improvement Using AI Tools
Cross-Functional Collaboration

Portfolio Artifacts

Sample Requirement Document (BRD Excerpt)

Project: AI-Based Sales Forecasting System

Business Objective: Improve monthly sales forecast accuracy and reduce inventory losses.

Stakeholders: Sales Head, Operations Manager, IT Lead
Current Problem: Manual forecasting with low accuracy
Proposed Solution: ML-powered forecasting dashboard
Functional Requirements:
- System shall import sales data automatically
- System shall generate monthly forecasts
- System shall display trends and alerts
Non-Functional: Data refresh < 5 min, 99% uptime

Business Intelligence Dashboard

Tool: Power BI

Purpose: Monitor sales, revenue, and customer performance

KPI: Monthly Revenue, Growth %, Churn Rate
Interactive filters by region and product
Automated daily refresh
Drill-down views for managers

Impact: Reduced reporting time by 40%

Process Model (BPMN Style)

Process: Customer Complaint Resolution

Customer submits complaint
System creates ticket
Support team reviews issue
Technical team investigates
Resolution sent to customer
Feedback collected

Improvement: Reduced resolution time by 25%

Problem → Solution Case Study

Project: Customer Retention Improvement

Problem:

High customer churn (22%)
No visibility into customer behavior

Analysis:

Conducted stakeholder interviews
Analyzed CRM and usage data
Identified churn triggers

Solution:

Built churn prediction model
Designed retention dashboard
Created automated alerts

Result:

Churn reduced to 14%
Revenue increased by 12%
Improved customer satisfaction

Resume

You can download my latest resume below:

📄 Download Resume (PDF)

Note: Upload your resume PDF in the same folder as this website.

Project Screenshots

Sales Forecast Dashboard

Screenshot of Power BI dashboard showing revenue trends and forecasts.

Impact: Improved sales forecast accuracy by 22%, reduced inventory overstock, and enabled leadership to make data-driven planning decisions.

Customer Analytics Report

AI-driven churn analysis and segmentation dashboard.

Impact: Identified key churn drivers and customer segments, contributing to an 8% reduction in churn through targeted retention strategies.

Process Mapping Tool

BPMN workflow created using Visio/Lucidchart.

Impact: Streamlined customer complaint resolution workflow, reducing turnaround time by 25% and improving cross-team clarity.

Interview STAR Stories

Improving Forecast Accuracy

Situation: Manual sales forecasting caused losses.

Task: Improve prediction accuracy.

Action: Built ML model and dashboard.

Result: Accuracy improved by 22%.

Reducing Customer Churn

Situation: High churn rate.

Task: Identify churn drivers.

Action: Performed data analysis and AI modeling.

Result: Churn reduced by 8%.

Automating Reports

Situation: Manual reporting took 10+ hours/week.

Task: Automate dashboards.

Action: Built Power BI pipelines.

Result: Saved 40% effort.

ATS Keywords & Competencies

Business Analysis Requirement Gathering BRD / FRD User Stories Agile Scrum SQL Power BI Data Analytics Machine Learning Stakeholder Management Process Improvement UAT JIRA Documentation AI Automation

Contact

Email: vidhudiaashish@gmail.com

LinkedIn: www.linkedin.com/in/aashishvidhudi

GitHub: https://github.com/ASH2408/Aashish.V

Location: Open to Remote & On-site Opportunities