HENRY JR Cabang's Work | ContraWork by HENRY JR Cabang
HENRY JR Cabang

HENRY JR Cabang

SAP MM/WM & Power BI Specialist | Inventory & Supply Chain

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HENRY JR is ready for their next project!

Followed by Ahmad A and GALLERY L

Makati, Philippines

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Makati, Philippines

### 🍍 Fruit Sales Data Analysis – Interactive Power BI Dashboard An interactive Power BI dashboard designed to analyze fruit sales performance and provide clear graphical insights into revenue, sales volume, product, size, and geographic performance. The dashboard includes: Sales Revenue – total revenue generated from fruit sales Total Sales Quantity – total quantity of fruits sold Sales by Fruit Name – compares sales performance across different fruits Sales by Size – analyzes sales across different fruit sizes Sales by City – identifies sales performance by city Sales by Country – compares sales across countries Sales per Month – monitors monthly sales performance Revenue per Month – tracks monthly revenue trends Sales Trend by Fruit – analyzes monthly sales trends by fruit name Geographic Sales Analysis – identifies locations with the highest and lowest sales performance The interactive dashboard allows users to explore product, size, time, and geographic sales patterns, helping identify top-performing fruits and markets while supporting data-driven sales and business decisions. Key value: Sales data → KPI analysis → Product & size analysis → Geographic analysis → Monthly trends → Graphical insights → Business decisions
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An interactive Power BI dashboard designed to monitor pineapple production and packing performance from 2019 to the present year. The dashboard provides graphical insights into: Total Pineapple Boxes Packed – overall production/packing volume Daily, Weekly, Monthly, and Yearly KPIs – performance monitoring across different time periods Packing Trends – identifies production trends and changes over time Brand Distribution – boxes packed by brand Tag Distribution – analysis of packing tags Variant Distribution – comparison of different pineapple variants Pack Size Distribution – analysis of boxes packed by pack size Time-Based Analysis – allows users to drill into daily, weekly, monthly, and yearly performance The dashboard helps management quickly understand packing volume, production trends, and product mix, while identifying changes in brand, tag, variant, and pack-size distribution. Key value: Production data → KPI analysis → Trend analysis → Product mix → Graphical insights → Better operational decisions
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An interactive Power BI dashboard designed to provide clear graphical insights into coffee sales performance and customer purchasing patterns. The dashboard analyzes: Total Sales – overall coffee sales performance Total Cups Sold – total number of cups sold Monthly Sales KPI – tracks sales performance by month Sales by Month – identifies monthly sales trends Sales by Time of Day – compares morning, afternoon, and evening/night sales Sales by Product – identifies which coffee products generate the highest sales Product Performance by Time of Day – shows which coffee products perform best during morning, afternoon, or night The interactive visuals make it easy to identify top-selling coffee products, peak sales periods, and monthly performance trends, helping management understand customer purchasing behavior and make better sales decisions. Key value: Sales data → KPI analysis → Interactive visualization → Customer insights → Better sales decisions
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An interactive Power BI dashboard designed to monitor and analyze carton wastage and its cost impact against the Annual Operating Plan (AOP). The dashboard provides daily, weekly, monthly, and yearly analysis of: Carton wastage and quantity trends Wastage cost impact vs. AOP Causes of damage and their contribution to total wastage Team performance, including the team with the highest damage Daily, weekly, monthly, and yearly trends Interactive buttons for easy navigation between different time periods Power BI Q&A page for users to ask questions and explore the data interactively The dashboard transforms raw operational data into clear graphical insights, helping management identify major wastage drivers, monitor trends, compare actual performance against AOP, and determine areas that require corrective action. Key value: From wastage data → KPI analysis → graphical visualization → business insights → actionable decisions.
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