Logesh V

Project #1

Client: Zensar Technologies

Role: Power BI Data Analyst

Environment: Power BI, SQL server, Salesforce, Excel.

Project Description:

I developed a comprehensive Sales Analytics Dashboard in Power BI for Zensar Technologies' retail client. The solution provided visibility into regional sales performance, customer acquisition trends, product-wise revenue, and sales pipeline tracking. I integrated multiple data sources including SQL Server, Excel, and CRM systems, and built interactive dashboards with drill-through and slicer functionalities. The solution enabled sales managers to track KPIs like revenue growth, conversion ratio, and sales rep performance, leading to a 15% improvement in forecast accuracy and better decision-making on resource allocation.

Responsibilities:

• Designed and developed Sales Analytics Power BI dashboards to track regional performance, product revenue, customer acquisition, and pipeline metrics.
• Gathered business requirements and translated them into scalable BI solutions , improving sales analysis and reporting accuracy.
• Built and optimized data models by integrating sources from SQL Server, Excel and CRM systems into a unified warehouse.
• Applied Power Query, Power Pivot, and advanced SQL for data transformation, validation, and performance optimization.
• Developed interactive dashboards with drill-through, slicers, and custom visuals, improving user experience and analytical depth.
• Defined and monitored KPIs such as revenue growth, sales conversions, and sales rep productivity, supporting performance tracking.
• Improved forecasting accuracy by 15% through actionable insights that enabled better resource allocation and business planning.
• Performed unit testing, report validation, and performance tuning , reducing report load times by 30%+ .
• Published and managed reports on Power BI Service , ensuring secure sharing, scheduled refresh, and enterprise accessibility.
• Collaborated with stakeholders and sales managers to resolve data/reporting issues and deliver faster, insight-driven decisions .

Project #2

Client: Sonata Software

Role: Power BI Data Analyst

Environment: Power BI, SQL, SAP, Salesforce.

Project Description:

For Sonata Software's manufacturing client, I built a Sales & Marketing Performance Dashboard in Power BI. The solution consolidated data from SAP, Salesforce CRM, and Excel reports to analyze campaign effectiveness, lead-to-deal conversion, product category sales, and market share by geography. I implemented DAX measures for YoY comparison, dynamic segmentation of high-value customers, and trend analysis. The solution helped the client's sales leadership identify underperforming regions, optimize campaigns, and boost marketing ROI by 12%.

Responsibilities:

• Built and deployed Power BI Sales & Marketing Performance Dashboards by integrating data from SAP, Salesforce CRM, Excel, SQL enabling unified business insights.
• Designed data models, Power Pivot calculations, and advanced DAX measures for year-over-year tracking, customer segmentation, and trend analysis , enhancing analytical capabilities.
• Utilized Power Query Editor for data transformation, migration, and data validation , ensuring data accuracy and consistency across diverse data sources.
• Developed interactive dashboards and self-service reports with drill-down capabilities in Power BI Service , reducing manual reporting efforts for business teams.
• Automated reporting workflows using Advanced SQL queries and data warehousing principles , improving efficiency and scalability.
• Conducted unit testing and reporting validation to maintain accuracy and strengthen trust in decision-making dashboards.
• Delivered actionable insights on campaign effectiveness, lead-to-deal conversions, product-category sales, and market share , influencing growth strategies.
• Partnered with stakeholders to translate business problems into analytical solutions, reports, and KPIs , directly contributing to a 12% increase in marketing ROI.

Project #3

Client: Mindtree (now LTIMindtree)

Role: Power BI Data Analyst

Environment: Power BI, SQL, Salesforce, SAP, Oracle, Excel.

Project Description:

I worked on a Financial Planning & Forecasting Dashboard for LTIMindtree's BFSI client. The solution aimed at automating P&L tracking, expense analysis, and budget vs actuals monitoring. I connected data from SAP HANA, Oracle ERP, and Excel templates into Power BI, applying Row-Level Security (RLS) for finance managers and executives. The dashboard provided real-time financial health monitoring with KPIs such as revenue variance, cost breakdowns, profit margins, and forecast accuracy. This reduced the client's manual reporting time by 30% and improved financial decision-making with timely insights.

Responsibilities:

• Designed and delivered a Financial Planning & Forecasting Dashboard in Power BI by gathering requirements from finance stakeholders and aligning KPIs with business objectives.
• Automated P&L tracking, expense analysis, and budget vs. actuals monitoring , reducing manual financial reporting efforts by 30% .
• Performed data migration and integration from multiple systems ( SAP HANA, Oracle ERP, Excel templates ) into a unified Power BI data warehouse .
• Built optimized data models using Power Pivot, DAX measures, and Power Query Editor , improving dashboard performance and forecast accuracy.
• Implemented Row-Level Security (RLS) in Power BI to enable tailored access control for executives and finance managers.
• Created interactive dashboards highlighting revenue variance, cost breakdowns, profit margins, and forecast KPIs , empowering real-time decision-making.
• Conducted data validation and unit testing ensuring accuracy, reconciliation, and transparency in financial reporting.
• Published and maintained dashboards via Power BI Service , leveraging proper Power BI Architecture (App Workspaces, Gateways, scheduling) .
• Partnered with finance teams to improve KPI definitions, enhance reporting accuracy, and establish business-wide financial transparency.
• Applied strong expertise in SQL (Advanced Queries, Joins, CTEs, Stored Procedures) for financial data transformation and ad-hoc reporting.
• Delivered solutions ensuring problem management, issue resolution, and performance optimization of reporting systems.