Garv Chanana

Data Analytics and Business Intelligence enthusiast

Delhi 0+ yrs exp 85 · Excellent

About

Data Analytics and Business Intelligence enthusiast with hands-on experience in developing interactive dashboards, predictive models, and data-driven solutions. Proficient in Python, SQL, Power BI, MySQL, and machine learning, with experience in data modeling, feature engineering, KPI development, and business analysis. Skilled at transforming complex datasets into actionable insights that support decision-making, performance optimization, and customer-focused strategies.

Skills & Expertise (24)

Python Intermediate

7.4/10

Years Exp

Pandas Intermediate

7.4/10

Years Exp

scikit-learn Intermediate

7.4/10

Years Exp

SQL Intermediate

6.5/10

Years Exp

Data Visualization Intermediate

6.0/10

Years Exp

Matplotlib Intermediate

6.0/10

Years Exp

Data Cleaning Intermediate

6.0/10

Years Exp

Feature Engineering Intermediate

6.0/10

Years Exp

NumPy Intermediate

6.0/10

Years Exp

Power BI Intermediate

5.5/10

Years Exp

Data Modelling Intermediate

5.0/10

Years Exp

Power Query Intermediate

5.0/10

Years Exp

Seaborn Intermediate

5.0/10

Years Exp

Advanced Excel Intermediate

5.0/10

Years Exp

Dashboard Design Intermediate

5.0/10

Years Exp

Data Interpretation Intermediate

5.0/10

Years Exp

Statistical Analysis Intermediate

5.0/10

Years Exp

DAX Beginner

4.5/10

Years Exp

SQL optimization Beginner

4.0/10

Years Exp

KPI development Beginner

4.0/10

Years Exp

Requirement gathering Beginner

4.0/10

Years Exp

Business Process Analysis Beginner

4.0/10

Years Exp

Stakeholder Reporting Beginner

4.0/10

Years Exp

MySql

Work Experience

Data Analytics Intern

IBM SkillsBuild - CSRBOX

Jun 2024 - Aug 2024

Contributed as part of a 5-member team to develop an Urban Heat Island Detection system by performing dataset analysis, data validation, and feature engineering on satellite imagery, and applying supervised and unsupervised ML models using Python and Scikit-learn to identify temperature hotspots and quantify their correlation with vegetation loss.