PowerBI
Project
Me
I’m a Data Analyst with a strong focus on transforming raw data into meaningful business insights. Currently working as a Marketing Campaign Analyst at EXL, I specialize in analyzing campaign performance, identifying trends, and driving data-backed decisions.
With hands-on expertise in Excel, Power BI, SQL, and Python, I bring both analytical depth and practical problem-solving to every project I work on. My approach goes beyond just reporting numbers—I aim to uncover the “why” behind the data and translate it into actionable strategies.
I hold a Bachelor’s degree in Computer Applications, which built the foundation for my analytical and technical skills. Alongside my professional experience, I’ve worked on multiple business-focused projects that demonstrate my ability to apply data analysis in real-world scenarios—each showcased in this portfolio.
I’m passionate about continuous learning and using data to create impact, and I’m always open to opportunities where I can contribute, g
Skills
POWERBI
EXCEL
SQL
Projects
Domain/Function: Sales Analytics
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Experience
EXL Services - Senior Associate | Audience Segmentation and Analytics
Cochin 07/2023 – Present
• Spearheaded audience targeting and segmentation operations across the enterprise, developing and executing strategies and best practices via the Salesforce CRM platform to enhance the client's go-to-market initiatives, resulting in a 25% improvement in campaign targeting efficiency.
• Monitored and assessed the effectiveness of segmentation efforts by directly interacting with clients, driving a 15% increase in customer satisfaction through data-driven insights that optimized their experience
• Transformed complex data into clear, actionable recommendations for stakeholders by utilizing Power BI and Excel dashboards, enabling data-driven decision-making and enhancing business outcomes.
• Identified and implemented optimization opportunities within the Marketing Cloud environment by creating automation and leveraging SQL queries, streamlining business processes and reducing inefficiencies by 20%, thereby enhancing operational productivity