Healthcare Clinical Insights | Power BI Dashboard
This Clinical Insights dashboard explores the clinical characteristics of patient encounters, bringing together information on diagnoses, severity, encounter types, vital signs, laboratory results, chronic conditions, procedures, and follow-up patterns.
It helps transform clinical records into a more structured view of patient populations, presenting insights that can support clinical monitoring, healthcare planning, and informed decision-making.
Key areas of analysis include:
Diagnosis Analysis: Identifies the most frequently recorded diagnoses and understand how clinical conditions are distributed across encounters.
Patient Acuity & Severity: Examines the severity of recorded cases and understand the distribution of patients across different acuity levels.
Encounter Types: Explores the different types of healthcare encounters and how clinical activity is distributed.
Vital Signs Analysis: Examine srecorded vital signs to identify patterns and variations across patient encounters.
Laboratory Results: Explores laboratory findings and their distribution across recorded clinical encounters.
Chronic Conditions: Understands the prevalence and distribution of recorded chronic conditions within the patient population.
Procedures & Interventions: Analyses the types and frequency of procedures recorded during encounters.
Admissions & Follow-up: Explores patterns in hospital admissions, follow-up requirements, and continuity of care.
With interactive filters and multiple dimensions of clinical analysis, users can explore specific diagnoses, compare patient groups, and investigate patterns across reporting periods.
The bigger picture: Clinical data holds valuable information beyond individual patient records. When properly organised and analysed, it can help healthcare organisations understand disease patterns, monitor patient acuity, evaluate clinical activity, and identify areas that may require further attention.
Built with Power BI, this dashboard demonstrates how business intelligence can make complex healthcare data more accessible, meaningful, and useful for clinical and administrative decision-making.
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Road Safety Analysis | Python, SQL & Power BI
Developed an end-to-end road safety analytics project to help authorities understand accident patterns, identify high-risk areas, and make informed decisions about road safety interventions.
The project involved cleaning and preparing road accident data using Python and Pandas, followed by SQL-based exploratory analysis to investigate accident trends, casualty figures, severity distributions, and geographical patterns.
Using Power BI, I transformed the findings into an interactive dashboard featuring key performance indicators and visualisations that provide an overview of accident activity, highlight trends over time, and reveal differences in accident occurrence across districts and locations.
The analysis also explored accident severity in relation to road types, weather conditions, lighting, and road surface conditions.
Tools used: Python, Pandas, SQL, Power BI.
Project deliverable: An interactive Power BI dashboard supported by data cleaning, transformation, and SQL analysis.
The objective was to turn raw accident data into clear, meaningful insights that can support evidence-based road safety planning and resource prioritisation.
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I Turned 4,000 projects ($4.57bn portfolio) into a 3-part risk dashboard
Key findings:
1. $2.26bn (49%) of budget is at risk, 762 projects flagged Critical
2. Risk doesn't fade as projects mature, it spikes again at Execution
3.Surprisingly, Senior/Mixed teams showed the highest critical-risk concentration, not Juniors meaning process maturity mattered more than experience
4.Budget utilization is highest at Initiation (~97%) and drops by Execution (~94%), the riskiest financial calls happen earliest, with the least information.
Built end-to-end in Power BI.
I help teams turn messy project, ops, or sales data into dashboards that actually drive decisions.
📩 Open to freelance and full-time work in data analytics & project management.
#DataAnalytics #PowerBI #ProjectManagement #RiskManagement #OpenToWork
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🚗 Executive Automotive Industry Intelligence — Powered by Power BI
How do the world's leading automotive manufacturers compare when it comes to revenue, profitability, production, and market performance?
At Intersect Analytics, we developed this executive Power BI dashboard to transform complex automotive industry data into a single source of truth for strategic decision-making.
📊 Executive Insights
Our analysis revealed several key industry trends:
🏆 Toyota Motor Corporation continues to lead the global automotive market, generating the highest revenue while maintaining exceptional profitability and vehicle production volumes.
📈 Volkswagen Group remains one of the strongest global competitors, demonstrating consistent revenue growth and a diversified international market presence.
⚡ BYD has emerged as one of the fastest-growing manufacturers, driven by rapid expansion in electric vehicle production and increasing global demand.
💰 While several manufacturers generate significant revenue, profit margins vary considerably, highlighting differences in operational efficiency, manufacturing costs, and pricing strategies.
🌍 Asian manufacturers continue to dominate the global automotive industry, contributing the largest share of revenue and vehicle production compared to Europe and North America.
🚘 The transition toward electric and hybrid vehicles is reshaping the competitive landscape, with manufacturers investing heavily in next-generation mobility technologies.
📉 Comparing Revenue against Cost of Sales reveals that companies with stronger cost control consistently deliver higher profitability despite operating in the same competitive environment.
📊 Revenue per vehicle varies significantly across manufacturers, reflecting differences in brand positioning, product mix, and premium versus mass-market strategies.
What This Dashboard Delivers
✔ Executive KPI Scorecards
✔ Revenue & Profitability Benchmarking
✔ Global Vehicle Sales Analysis
✔ Regional Performance Comparison
✔ Revenue vs Cost Analysis
✔ Net Profit Margin Analysis
✔ EV, Hybrid & ICE Market Breakdown
✔ Interactive Geographic Performance Mapping
✔ Executive-ready Multi-page Reporting
Our Services
At Intersect Analytics, we help organizations transform raw business data into executive intelligence through:
✅ Power BI Dashboard Development
✅ Financial Analytics & Executive Reporting
✅ Business Intelligence Solutions
✅ Excel & Google Sheets Automation
✅ SQL Data Modeling & ETL
✅ Power Query & DAX Optimization
✅ KPI Scorecards & Performance Monitoring
✅ Predictive Analytics & Decision Support
Every dashboard we build is designed to help leaders move beyond reporting—to uncover trends, optimize performance, and make confident, data-driven decisions.
📊 Decisions Backed by Data. Growth Driven by Insight.
If your organization is ready to unlock the full potential of its data, let's build a solution tailored to your business.
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This is a snippet of a research report i have written on intermittent fasting. I have the proposal, the data analysis and the interpretation of the results
I will do excellent research on any topic subject, data analysis with python and spss, nursing, write dissertation, graphic design and complete any class assignments. Reach out for quality work and timely delivery.
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Conducted strategic business research analyzing market trends, competitors, and opportunities to provide actionable insights that supported informed decision-making and growth planning.
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Bulk Data Cleansing
Title: Multi-Source CRM Contact Database Standardization
Project Description:
Scrubbing and consolidating messy consumer data lists compiled across multiple event sign-up forms and legacy sheets into a single, clean master file ready for database migration.
What I Did:
Executed deep deduplication across 15,000 rows of raw customer contact text records.
Normalized phone numbers into standard international formats and fixed mismatched date structures.
Cleaned up text columns by fixing typos, capitalizing names, and separating merged text fields.
The Result: Delivered a 100% error-free, tabular dataset ready for smooth CRM integration without any broken entries.
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Q. How do you ensure annotation quality?
A. Every dataset is reviewed for accuracy and consistency before delivery, following your labeling guidelines.