In a world driven by data, I specialise in transforming complexity into clarity. With a solid foundation in Business Analytics and a proven track record of delivering actionable insights, I help organisations make data-driven decisions that drive growth and efficiency. I combine technical expertise, business acumen and a passion for problem-solving to deliver solutions that matter.
As a Master’s graduate in Business Analytics from Monash University, I bring a unique blend of technical skills and business understanding to the table. Whether it’s designing predictive models, creating interactive dashboards or streamlining workflows, my focus is always on achieving measurable outcomes.
Here’s how I make an impact:
- Turning raw data into strategic insights for better decision-making.
- Building robust data pipelines and visualisation tools to simplify complex problems.
- Delivering solutions tailored to business needs, with precision and clarity.
Data Analytics
- Python, R, SQL, Advanced Excel
- Data processing, statistical analysis, predictive modelling
Data Visualisation
- Tableau, Power BI, R Shiny
- Dynamic dashboards, interactive visualisations, trend analysis
Business Intelligence
- Decision support systems, forecasting, KPI tracking
Tools and Frameworks
- Pandas, NumPy, Matplotlib, ggplot
- Jupyter Notebooks, GitHub, Agile workflows
An R package developed to automate the extraction, processing and analysis of academic publication data from ORCID and Google Scholar IDs, enhancing data retrieval and reporting efficiency.
- Key Highlights:
- Built a robust pipeline for seamless data integration, enabling efficient analysis and reporting.
- Analysed over 2,000 academic publications to uncover key trends and performance metrics.
- Simplified the visualisation of research outputs through dynamic analytical plots, supporting data-driven strategic planning.
A Python-powered system designed to help users find their ideal property based on geospatial data and personalised preferences.
- Key Highlights:
- Built a suitability scoring algorithm using property features and geospatial proximity to amenities.
- Integrated haversine formula to calculate real-time distances to essential services like schools and train stations.
- Delivered actionable insights through visualisation dashboards.
An R Shiny application designed to uncover trends in coffee brand popularity and outlet distribution.
- Key Highlights:
- Designed user-friendly interfaces for trend analysis and market insights.
- Implemented feedback analysis using word clouds to highlight customer preferences.
- Enabled dynamic filtering and customisation for in-depth analysis.
If you’re looking for someone who can elevate your data capabilities or help solve a challenging problem, I’d love to connect.
- LinkedIn: linkedin.com/in/parnikakhattri
- Email: [email protected]
Data is everywhere; let’s harness its power together.