Data anlayst

Note: This is an AI-generated image and not an actual dashboard.

The aim of this project was to empower a Farming Industry with a dynamic Power BI dashboard to monitor and analyze employee working hours and payroll distribution across departments, employees, tasks, and timeframes. The solution was designed to provide actionable insights into labor costs and workforce efficiency by integrating multiple disconnected Excel tables. Leveraging dynamic measures, drill-through functionality, and custom logic for KPIs, the dashboard enabled the client to interactively explore paid hours, idle time, utilization, and departmental breakdowns. Despite evolving requirements, the project was delivered on time, enhancing visibility and decision-making around employee productivity and cost optimization.

Industry	Technology Used	Problem Statement	Solution	Impact
Farming & Agriculture	Power BI, Excel	Need a comprehensive Power BI dashboard to analyze employee work hours, including payroll data across departments, employees, days, and subtasks. The challenge was to accommodate data from disconnected Excel tables, with no relationships, and to provide drill-through functionality.	Designed a four-tab dashboard architecture with drill-through functionality for dynamic analysis at department, employee, day, and subtask levels. Used DAX measures to link data across tables for accurate KPI calculation.	The dashboard enabled to perform real-time, detailed analysis of working hours, cost allocation, and resource utilization at various levels. It improved decision-making around workforce management and payroll allocation, leading to optimized productivity and cost savings.
		There were multiple KPIs such as Paid Hours, Department Hours, Additional Hours, Task Hours, Location Hours, Idle Time, Utilization %, and Efficiency, but the logic requirements for these KPIs changed 4-5 times during the project.	Created dynamic measures to calculate the KPIs, adapted to the client’s changing requirements. Despite the frequent changes, ensured that the measures were updated quickly, and performed thorough QA to guarantee accurate results.
		Required the ability to analyze work hours by week and year, with a flexible and interactive format.	Implemented slicers and dynamic measures to allow users to select a specific week or year and analyze the data interactively for that time period.
		The data source in Excel had multiple disconnected tables, which made it difficult to relate employees, departments, and their working hours.	Used DAX functions like LOOKUPVALUE and relationships in the model to connect data across the multiple disconnected tables and ensure accurate KPI calculation.
		The dashboard needed to support real-time adjustments, allowing users to drill down from department-level insights to subtask-level details.	Implemented drill-through functionality to allow seamless navigation from department-level to employee-level, day-level, and finally subtask-level insights, making the dashboard highly interactive.