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Bridging the Zero Trust Execution Gap
Evidence-Based Cybersecurity Research & Enterprise Roadmap
Zero Trust has moved from a cybersecurity concept to an enterprise security priority. But many organizations still struggle to turn the architecture into a practical implementation plan.
This project investigates that execution gap and translates complex Zero Trust principles into a practical, NIST-aligned enterprise roadmap.
What I researched and developed
An evidence-based analysis of the Zero Trust implementation gap
NIST SP 800-207 and CISA-aligned security architecture
Identity, device, network, application, and data security considerations
Non-human identity risks, including service accounts, API keys, and AI agents
An 18–36 month phased implementation roadmap
Industry-specific considerations for SaaS-heavy and financial-services environments
Business-risk implications of Zero Trust adoption
Visual comparison tables, implementation roadmaps, and decision-oriented frameworks
My Role
I worked as the cybersecurity researcher and sole author, turning technical security frameworks and enterprise security research into clear, decision-ready content for security leaders.
The project demonstrates my ability to take a complex technical subject, verify and organize the evidence, and turn it into a structured piece of research that connects cybersecurity architecture with business risk and implementation.
Full whitepaper: [Link will be added here]👇
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Finding the right job often requires manually comparing a resume against dozens of job descriptions.
This project automates that process by:
Analyzing a resume against multiple real job postings
Generating AI-powered match scores
Identifying missing skills
Providing resume improvement suggestions
Storing results in a SQL database
Visualizing insights in Power BI
Offering a live Streamlit web application
🛠️ Tech Stack
Python
Pandas
SQLite
SQL
Google Gemini AI API
Streamlit
Power BI
VS Code
📊 Key Features
AI Resume Analysis
Resume-to-job match scoring (0–100%)
Missing skill identification
AI-generated recruiter feedback
Resume improvement recommendations
Database & SQL
Stores analyzed jobs in SQLite
Performs analytical queries
Identifies skill gaps
Finds best-fit companies and locations
Power BI Dashboard
Average Match Score
Strong Fit Jobs
Top Match Score
Company Match Analysis
Skill Gap Analysis
Streamlit Application
Paste any job description and instantly receive:
Match Score
Missing Skills
AI Feedback
Resume Improvement Tips
📈 Dashboard Insights
The dashboard provides:
Overall resume strength across jobs
Best matching companies
Skill gap analysis
Job fit distribution
Career improvement opportunities
🎯 Business Value
This project demonstrates:
Data Cleaning
Data Analysis
SQL Querying
AI Integration
Dashboard Development
Data Visualization
End-to-End Analytics Workflow
🔮 Future Improvements
Analyze 100+ job postings
Automated LinkedIn job ingestion
Multiple resume comparison
Industry-specific recommendations
Advanced skill trend tracking
👨💻 Author
Gourav Jangid
Aspiring Data Analyst passionate about transforming data into actionable insights using Analytics, SQL, Python, Power BI, and AI.
Awesome use case! Automating resume-job matching saves so much time.
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