Interactive BI Dashboards – Business Insights at a Glance

Mukesh Shirke
Aug 7
4 min read

Updated: Aug 15

Real-time visualization dashboards to uncover key business insights using Power BI and Tableau.

This project highlights a set of interactive dashboards created to analyze real-world datasets across HR, Sales, and Small Business domains. Designed with business stakeholders in mind, each dashboard delivers focused insights using dynamic filters, KPIs, and visual storytelling.

The goal was to convert raw data into actionable intelligence for data-driven decision-making.

Key Skills Demonstrated:

Data Cleaning & Transformation
Interactive Dashboard Design
Visual Analytics and Storytelling
Business Insight Extraction
UX for BI Tools
Advanced Filtering & DAX (Power BI)

Tools used:

Data Preparation: Excel, SQL
Data Visualization: Power BI, Tableau

Design Principles:

' Prioritized data over decoration '

Applied principles from Ben Shneiderman’s "Eight Golden Rules of Interface Design" to improve usability:

Ensured consistency in layout, filters, and color use
Designed with user control in mind (e.g., slicers, filters)
Offered informative feedback through KPIs and alerts
Simplified tasks by grouping relevant data visuals together
Focused on maximizing clarity by applying the low ink-to-data ratio principle. Removed unnecessary chart borders, labels, and gridlines to reduce visual noise

GitHub repository:

https://github.com/MukeshTheAnalyst/business-insights-bi-dashboards

PizzaRio Small Biz Dashboard (Power BI):

Purpose: Enable data-backed decision-making for a fictional pizza business across orders, inventory, and staffing.

Orders Dashboard

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Visual Features:

Hourly order trends (line chart)
Top-selling items (bar chart)
KPI cards: Total sales & average order value
Calendar filter for weekly/monthly drilldown

Key Insights:

Evening hours drive peak sales
Monthly promotions affect AOV
Delivery vs pickup trends vary by weekday

Inventory Dashboard

Visual Features:

Ingredient usage tables
Low-stock alert indicators
Inventory by pizza size
Supplier lead-time buffer planning

Key Insights:

Automated stock level alerts reduce out-of-stock risk
Ingredient usage data helps in cost optimization

Staff Dashboard

Visual Features:

KPI cards for total staff cost and labor per pizza
Chef vs Delivery staff split
Shift-based performance metrics

Key Insights:

Visual cost comparison aids better staffing decisions
Supports labor cost control and scheduling

Sales Dashboard – Product & Salesperson Performance (Power BI):

Purpose: Understand sales by category and evaluate individual salesperson contributions.

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Visual Features:

KPI cards for revenue, units sold
Filter applied to “Bikes” category
Tooltips on subcategories for deeper insight
Bar/line charts to compare salespersons

Key Insights:

Bikes subcategory drives a large share of revenue
Salesperson performance shows seasonal variation
Product-level trends highlight high-performing SKUs
Subcategory filter reveals hidden opportunities

HR Dashboard (Tableau):

Purpose: Offer an HR overview focusing on roles, demographics, and salary trends.

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Visual Features:

Bar chart for employee count by job title
Pie chart for gender distribution
Histogram for age spread
Top earners by job
Qualification vs Salary comparison
Staff growth trend over 5 years
Filter to explore staff by first letter

Key Insights:

High-paying roles clearly identified
Gender imbalance detected in certain departments
Younger demographic dominates entry-level roles
Hiring growth visible over time

Patient Waiting List Dashboard (Power BI):

Purpose: Offer a comprehensive view of patient waiting lists by combining high-level trends, case type distribution, age and specialty insights with detailed month-by-month data. This integrated approach supports both strategic planning and day-to-day operational decisions to address backlogs and improve healthcare service delivery.

Summary Dashboard

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Visual Features:

KPI cards for latest month, previous month, and prior year waiting list totals
Donut chart for case type split (Outpatient, Day Case, Inpatient)
Stacked column chart for time band vs. age profile
Top 5 specialties ranked by average/median wait list size
Specialty group count breakdown with tooltip view
Line charts showing trend over time for Day Case, Inpatient, and Outpatient volumes
Interactive filters for date range, case type, and specialty name
Toggle between average and median metrics

Key Insights:

Outpatient cases form over 72% of the waiting list
Longest waits (18+ months) are concentrated in the 16–64 age group
Paediatric ENT, Orthopaedic, and Dermatology have the highest average waiting lists
Noticeable rise in outpatient volumes post-2020, indicating backlog accumulation
Total waiting lists grew from ~624K to 704K in one year

Detailed Dashboard

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Visual Features:

Data table showing Day Case, Inpatient, Outpatient, and total counts per month
Grand totals for each case type and overall totals at the bottom
Filters for date range, case type, specialty name, age profile, and time bands
Scrollable monthly breakdown covering over 3 years of data

Key Insights:

Outpatient numbers increased steadily from ~502K in Jan 2018 to ~623K in Jan 2021
Day case volumes declined until early 2020, then recovered towards 2021
Inpatient counts remained relatively stable (~20K–24K)
COVID-19 period saw noticeable increases across all case types
Overall patient totals climbed from ~582K in 2018 to over 704K in 2021

Conclusion:

This project demonstrates how data visualization can power real-time, insight-driven decisions. Each dashboard is customized for end-user clarity, balancing aesthetics with business relevance. The use of Power BI features like tooltips, filters, and KPI cards ensures users focus on what matters most.