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kavyanjali-karan/README.md

Kavyanjali Karan

Business Intelligence · SQL · Python · Power BI · Reporting Systems
B.Tech Computer Science — ITER, SOA University (2027) · Bhubaneswar, India · Open to Relocate


What I Build

Business Intelligence starts long before dashboards.

I'm a Computer Science student building production-style Business Intelligence reporting systems that transform operational data into reliable reporting assets through SQL transformation, Python ETL, dimensional modeling, KPI governance, semantic modeling, and engineering documentation.

Across my repositories, the focus remains consistent: preparing trusted analytical datasets that support business metrics, executive reporting, and recurring business reviews. The dashboard is the final layer—not the starting point.


Featured Repositories

Repository Business Focus Reporting Outcome
Customer Retention Intelligence Platform Customer lifecycle reporting Curated analytical datasets, customer health reporting, cohort analysis, semantic modeling, API-enabled reporting, and executive KPIs.
Executive KPI Governance Platform Business performance reporting Standardized KPI definitions, governed business metrics, reporting standards, executive scorecards, and semantic reporting models.
Growth Funnel Performance Review Acquisition and conversion reporting Funnel analysis, governed business metrics, dimensional modeling, executive reporting, and recurring business reviews.
Marketplace Growth Performance Review Marketplace performance reporting Customer, seller, and product reporting supported by curated analytical datasets, Power BI reporting, and business recommendations.

Engineering Philosophy

Every repository follows the same reporting workflow.

Operational Data
        │
        ▼
SQL Transformation
        │
        ▼
Python ETL & Data Validation
        │
        ▼
Curated Analytical Datasets
        │
        ▼
Dimensional Modeling
        │
        ▼
Semantic Reporting
        │
        ▼
Executive Reporting

The objective is to organize business data into reporting systems that produce consistent, reusable business metrics instead of isolated dashboards.

Technical Foundation

Business Intelligence
Power BI · DAX · Power Query

Data Engineering
SQL · Python · ETL · Data Validation

Analytical Modeling
Dimensional Modeling · Star Schema · KPI Governance · Semantic Modeling

Reporting & Documentation
Executive Reporting · Business Documentation · Reporting Playbooks · Weekly Business Reviews

Tools
Git · GitHub · VS Code · Jupyter Notebook


What These Repositories Demonstrate

Rather than presenting individual dashboards, each repository focuses on a different part of the Business Intelligence reporting lifecycle.

  • Designing reporting architectures around business requirements.
  • Transforming operational data into curated analytical datasets.
  • Building dimensional models for reusable reporting.
  • Defining governed business metrics and KPI standards.
  • Developing semantic reporting models in Power BI.
  • Supporting executive reporting with engineering documentation and reporting playbooks.

Together, these repositories demonstrate how reporting systems are designed before they are visualized.


Recognition

Programme Organisation Year
Forward Program — Selected McKinsey & Company 2026
GenAI Academy APAC — Selected Google 2026
DevTrails Hackathon — Seed 2 Qualifier Guidewire Software 2026
Techgium — National Round 2 Qualifier L&T Technology Services 2025
SQL Certification HackerRank 2025
SQL 50 LeetCode 2026

Certifications

  • Tata GenAI Powered Data Analytics — Forage
  • Deloitte Data Analytics Job Simulation — Forage
  • AWS Solutions Architecture Job Simulation — Forage
  • AI for Beginners — HP LIFE

Currently Learning

As I continue building Business Intelligence reporting systems, I'm deepening my understanding of:

  • Advanced SQL for analytical reporting
  • Data warehouse design
  • Power BI semantic models
  • KPI governance
  • Reporting architecture
  • Business metric design
  • Dimensional data modeling

Looking Ahead

I'm interested in Business Intelligence Engineering roles where reporting is treated as an engineering discipline rather than a visualization task. My current work focuses on designing reporting systems that organize operational data into trusted analytical models for executive reporting and business decision-making.

I'm continuously expanding this portfolio by building reporting solutions across different business domains while strengthening my understanding of data warehousing, semantic modeling, and modern BI engineering practices.


Let's Connect

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Building production-style Business Intelligence reporting systems that transform operational data into governed analytical models for executive reporting and business decision-making.

Pinned Loading

  1. customer-retention-intelligence-platform customer-retention-intelligence-platform Public

    Customer retention reporting system built with SQL transformation, Python ETL, dimensional modeling, KPI governance, and Power BI executive reporting.

    Python 1

  2. executive-kpi-governance-platform executive-kpi-governance-platform Public

    Executive reporting system focused on governed business metrics, dimensional modeling, semantic reporting, and engineering documentation for consistent KPI reporting.

    Python 1

  3. growth-funnel-performance-review growth-funnel-performance-review Public

    Growth funnel reporting system measuring acquisition, activation, conversion, and retention through SQL transformation, curated analytical datasets, and executive reporting.

    Python 1

  4. Marketplace-Growth-Performance-Review Marketplace-Growth-Performance-Review Public

    Marketplace reporting system for customer, seller, and product performance using SQL transformation, dimensional modeling, and Power BI executive reporting.

    Python 1