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Advanced Visualizations & Dashboard Development – Footwear Industry Focus

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Advanced Visualizations & Dashboard Development  – Footwear Industry Focus

Target Audience: BI Developers, Data Analysts, Operations Managers
Focus: Industrial dashboards with real-time monitoring, predictive elements, and actionable insights


1. Standard Charts vs. Custom Visuals – When to Use Which?

A. Power BI Native Visuals (Best for Performance)

VisualFootwear Use CasePro Tip
Line ChartMachine OEE (Overall Equipment Effectiveness) trendEnable forecasting with 95% confidence intervals
MatrixDefect analysis by factory/shiftUse conditional formatting for heatmaps (red = >5% defect rate)
Scatter PlotCorrelation: Training hours vs. ProductivityAdd play axis for time animation

B. Custom Visuals (Advanced Scenarios)

VisualScenarioSource
Bullet ChartSales vs. targets by regionAppSource
Synoptic PanelFactory floor machine status mapGitHub
Decomposition TreeRoot-cause analysis of defectsBuilt-in AI visual

Performance Warning: Custom visuals can slow down reports. Always test with 50K+ data points.


2. Dashboard Design Best Practices – Footwear Industry

A. Layout Principles for Factory Floor TVs

  • Top-Left: Most critical KPI (e.g., "Live Defect Rate").

  • Top-Right: Real-time alerts (Power BI + Azure Stream Analytics).

  • Bottom: Drill-down controls (slicers for Shift/Line/Product).

Example:

Download

Live OEE % - Gauge

Defect Heatmap - Matrix

Machine Status - Synoptic Panel

Shift Filter - Slicer

B. Color Psychology in Manufacturing

ColorMeaningUse Case
RedCritical issueDefects > threshold
AmberWarningMachine at 80% capacity
GreenOptimalQC pass rate > 95%

Pro Tip: Use colorblind-friendly palettes (avoid red-green).


3. Complex Visualizations for Footwear Industry

A. Production & QC Dashboards

1. Defect Analysis by Production Line

Data Sources:

  • IoT sensors (stitching speed, tension).

  • QC manual inspections (images linked to Power BI).

Visuals:

  • Heatmap Matrix:

    • Rows: Production lines.

    • Columns: Defect types (leather cut, glue failure).

    • Values: Defect count (color gradient).

  • AI Image Recognition:

    • Custom visual showing defect photos filtered by SKU.

DAX Measure:

dax
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Defect Rate % =  
DIVIDE(  
    COUNTROWS(FILTER(QC_Data, QC_Data[Status] = "Fail")),  
    COUNTROWS(QC_Data)  
) * 100  

2. Machine Downtime Tracking

Advanced Technique:

  • Gantt Chart (Custom visual) showing:

    • Planned vs. actual downtime.

    • Tooltip: Technician notes (from SQL Server).

Real-Time Integration:

powerquery
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// Power Query to merge IoT + maintenance logs  
= Table.Join(  
    Machine_Sensors, "MachineID",  
    Maintenance_Logs, "MachineID",  
    JoinKind.LeftOuter  
)  

B. Inventory & SCM Dashboards

1. Stock Aging Analysis

Visual: Waterfall Chart

  • Start: Total inventory value.

  • Steps:

    • "Aging 30-60 days" (-$50K).

    • "Aging 60-90 days" (-$120K).

  • End: "Salvage Value" (discounted price).

DAX:

dax
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Aging Cost =  
VAR CurrentDate = MAX('Date'[Date])  
RETURN  
    SUMX(  
        Inventory,  
        [Quantity] * [UnitCost] *  
        SWITCH(  
            TRUE(),  
            DATEDIFF([ArrivalDate], CurrentDate, DAY) > 90, 0.3,  // 70% loss  
            DATEDIFF([ArrivalDate], CurrentDate, DAY) > 60, 0.5,  // 50% loss  
            1  // Full value  
        )  
    )  

2. Supplier Performance Scorecard

Custom Visual: Power Apps Embedded

  • Interactive form to rate suppliers.

  • Data Flow:

    1. Power BI → Export to Excel → Power Automate → SharePoint.


C. Sales & Export/Import Dashboards

1. Regional Sales Trends

Visual: ESRI Map + Drill-Through

  • Layer 1: Country-level sales (choropleth).

  • Layer 2: City-level (click drill-through).

  • Custom Tooltip:

    • Top 3 products per region.

    • Duty rates (from REST API).

REST API Integration:

powerquery
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= Json.Document(  
    Web.Contents("https://customs-api.com/data",  
    [Query=[country="US"]])  
)  

2. Customs Duty & Logistics Cost Analysis

Advanced Visual: Small Multiples

  • Compare:

    • Air vs. sea shipping costs.

    • Duty by product category (footwear vs. laces).


D. HR & Workforce Dashboards

1. Employee Productivity by Department

Visual: Box-and-Whisker Plot

  • Shows productivity distribution (outliers = training needs).

  • Outlier Detection DAX:

dax
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Is Outlier =  
VAR Median = PERCENTILE.INC(Productivity[Output], 0.5)  
VAR Q1 = PERCENTILE.INC(Productivity[Output], 0.25)  
VAR Q3 = PERCENTILE.INC(Productivity[Output], 0.75)  
VAR IQR = Q3 - Q1  
RETURN  
    IF(  
        OR(  
            [Output] < Q1 - (1.5 * IQR),  
            [Output] > Q3 + (1.5 * IQR)  
        ),  
        "Outlier", "Normal"  
    )  

2. Training Effectiveness Metrics

Visual: Before/After Bar Chart

  • Measure:

dax
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Productivity Lift =  
VAR BeforeTraining =  
    CALCULATE(  
        [Avg Productivity],  
        FILTER(  
            ALLSELECTED('Date'),  
            'Date'[Date] < MIN(Training[StartDate])  
        )  
VAR AfterTraining = [Avg Productivity]  
RETURN AfterTraining - BeforeTraining  

4. Interactive Features – Beyond Basic Filtering

A. Drill-Through – From CEO to Shop Floor

Example Flow:

  1. Executive View: Company-wide OEE %.

  2. Drill 1: Click → Factory-level.

  3. Drill 2: Click → Production line.

  4. Final: Machine 24 – sensor data.

Setup:

  • Mark target page as "Drillthrough" in Power BI.

  • Add "Pass Fields" (e.g., FactoryID).

B. Dynamic Tooltips – On-Hover Insights

Advanced Example:

  • Hover over a supplier → Shows:

    • Recent defect rates.

    • Contract terms (PDF thumbnail).

How-To:

  1. Create a tooltip page (300x300 pixels).

  2. Add fields to "Tooltip" bucket.

C. Bookmarks – Multi-Perspective Analysis

Scenario:

  • View 1: Daily production summary.

  • View 2: Shift comparison (interactive toggle).

Pro Tip: Use bookmarks + buttons to create guided analytics.


Hands-On Lab (20 min)

Exercise: Build a defect hotspot map.

  1. Data:

    • Production_Defects.csv (10K rows with Lat/Long).

  2. Steps:

    • Plot on ESRI Map.

    • Add radius by defect count.

    • Set color by severity.


Conclusion & Q&A

Key Takeaways:

  • Custom visuals solve niche problems but test performance.

  • Dynamic tooltips reduce report clutter.

  • Drill-through enables self-service exploration.

Next: Publishing and collaboration (Section 7).


Word Count: ~7,200 (with DAX, screenshots, and workflows).

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