ICON Unit Weight Report Dashboard

Overview

In this project, I developed an end-to-end Power BI reporting solution to monitor and analyze unit weight data for the ICON product line. The data is collected from an Excel file received via email and systematically stored in the ICON Unit Weight Report table using Dataflows. This automated data collection process ensures that the reports are updated regularly, reducing manual intervention and increasing reliability.

The purpose of this dashboard is to help stakeholders gain insights into production quality and weight variations while providing interactive tools to explore the data across multiple dimensions. The ICON Unit Weight Report Dashboard offers a structured and visually appealing interface where users can view detailed information and key metrics derived from the underlying dataset.

Data Preparation and Storage:

The dataflow created in Power BI efficiently processes the incoming Excel data by cleaning, transforming, and loading it into the ICON Unit Weight Report table. This ensures that the dataset is ready for analysis without requiring repetitive data preparation tasks. The solution handles a large volume of records and ensures that data consistency is maintained over time.

Dashboard Overview:

The dashboard’s central component is a table visualization that displays the relevant data records, enhanced by calculated columns that provide additional analytical depth. These columns offer actionable insights and help users understand the production trends more effectively. The calculated columns implemented in this solution include:

• Count of Serial Numbers: Tracks the total number of units processed, helping users understand production volume.
• Sum of Weight Over: Calculates the total weight above the target, highlighting instances where units exceed acceptable weight limits.
• Sum of Weight Under: Represents the total weight below the target, helping teams monitor underweight production issues.
• Average of Actual Weight: Provides an overview of how the actual weight compares to expected values, assisting in quality assessment.
• Average of Standard Weight: Offers a reference for expected weight, enabling better comparison and variance analysis.
• Waste Dollar Over Target: Calculates the monetary impact of excess weight, helping in identifying potential areas where cost overruns occur due to weight deviations.

These calculated columns not only summarize the dataset but also allow users to track key performance indicators and investigate anomalies.

Interactive Filtering:

The dashboard includes a Filter Section on the left-hand side, giving users complete control over how they view the data. The available filters are:

• Date Filter: Users can select specific time periods to view data trends and patterns across days, weeks, or months.
• Brand Filter: Allows users to analyze data across different product brands to assess performance and weight variations.
• Plant Filter: Enables comparisons across manufacturing plants to identify location-based differences and address inconsistencies.
• Model Filter: Helps users drill down to specific models, making it easier to review unit-specific weight performance.

These filters ensure that users can slice and dice the data according to their needs without navigating away from the dashboard or requiring complex queries.

Business Impact:

The implementation of this Power BI dashboard has significantly improved reporting efficiency and data-driven decision-making. Key benefits include:

• Automation: With Dataflows, data is automatically updated without manual uploads, saving time and reducing errors.
• Enhanced Visibility: Stakeholders can easily monitor production quality and identify weight deviations that may affect operational efficiency.
• Data-Driven Insights: Calculated columns like waste dollar over target and average actual weight provide clear metrics that support decision-making.
• User Empowerment: Interactive filters allow users to customize reports based on their specific requirements, enhancing the user experience.

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This project reflects my ability to integrate automated data pipelines, create insightful visualizations, and develop interactive reports that provide both high-level summaries and detailed analysis. The Power BI solution I designed has streamlined reporting, improved operational awareness, and delivered actionable insights that support better decision-making across teams.

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