Graduate degree
MSc in Statistics
Patna University
MSc Statistics · Patna University
Hare Ram
Data Analyst | Python | SQL | Power BI | AWS
MSc graduate in Statistics with a strong quantitative foundation, focused on Data Analytics and Business Intelligence. I work with Python, SQL, Excel, Power BI, and AWS to clean, analyze, visualize, and transform data into actionable insights.
01 — About
About me
I am Hare Ram, an MSc Statistics graduate from Patna University with a strong foundation in statistics, quantitative analysis, and data interpretation.
I am building my career in Data Analytics and enjoy working with data to discover patterns, generate insights, and support business decisions.
My current focus includes Python, SQL, Excel, Pandas, NumPy, Power BI, Tableau, AWS, data pipelines, Databricks, and RAG-based applications.
I enjoy working on practical projects involving data cleaning, exploratory data analysis, visualization, dashboards, cloud services, and data pipelines.
02 — Education
Education
03 — Skills
Technical skills
Tools and methods I use in analysis, reporting, cloud work, and data pipelines.
Programming
Languages
Data analysis
Analysis
Visualization & BI
Reporting
Databases
SQL platforms
Cloud & AWS
Amazon Web Services
Data engineering
Pipelines
AI / GenAI
Applied AI
Tools
Daily tools
04 — Projects
Projects
Practical work across analytics, cloud architecture, pipelines, and document question answering.
01 · Analytics
Netflix Content & Viewership Analysis
An exploratory data analysis project focused on Netflix content, production trends, genres, viewership, movies vs TV shows, and audience patterns.
- Python
- Pandas
- NumPy
- Plotly
- Data Visualization
- Jupyter Notebook
Key work
- Data cleaning
- Exploratory data analysis
- Content and genre analysis
- Production trends and viewership analysis
- Interactive visualizations
02 · Analytics
YouTube Channel Analytics
A data analytics project that collects and analyzes YouTube channel information for Data Science, Data Analytics, and Data Engineering channels across different countries.
- Python
- YouTube API
- Pandas
- Excel
- Power BI
Key work
- Subscribers, total views, and video count
- Channel category, country, and creation date
- Data collection date tracking
- Dashboards for channel performance and country-wise comparisons
03 · Analytics
Flood Data Analysis
A data analysis project focused on compiling and analyzing flood-related information such as affected people, animals, agriculture, and other impact indicators.
- Python
- Pandas
- Excel
- Data Cleaning
- Data Visualization
- Power BI
Key work
- Collect multiple datasets and compile Excel files
- Clean inconsistent data and standardize columns
- Analyze affected populations and agricultural impact
- Create visual reports and dashboards
04 · Cloud
AWS S3 → Lambda → RDS Data Pipeline
A serverless AWS proof-of-concept where uploading a file to an Amazon S3 bucket triggers a Python Lambda function. The Lambda function processes file metadata and stores the information in an Amazon RDS MySQL database.
ArchitectureS3 → Lambda → RDS MySQL → CloudWatch
- Amazon S3
- AWS Lambda
- Python
- Amazon RDS
- MySQL
- IAM
- CloudWatch
Key work
- S3 ObjectCreated event and Lambda trigger
- File metadata extraction and database insertion
- IAM permissions and CloudWatch logging
05 · Cloud
AWS Public Application + Private Database VPC
A secure AWS VPC architecture where the application is publicly accessible through an internet-facing Application Load Balancer while the application server and RDS MySQL database remain in private subnets.
ArchitectureInternet → ALB → Private EC2 → Private RDS MySQL
SecurityALB-SG → App-SG → RDS-SG
- VPC
- Public Subnet
- Private Subnet
- Application Load Balancer
- EC2
- RDS MySQL
- Security Groups
- IAM
Key work
- Public entry through an internet-facing load balancer
- Application and database kept in private subnets
- Security group chaining and network boundaries
06 · Data engineering
Databricks E-commerce Data Pipeline
An e-commerce data pipeline following a Bronze, Silver, and Gold architecture for data ingestion, transformation, quality checks, and analytics.
ArchitectureRaw → Bronze → Silver → Gold → Power BI
- Databricks
- Python
- SQL
- ETL
- Data Quality
- Data Pipeline
- Power BI
Key work
- Data ingestion and transformation
- SQL analysis and data quality checks
- Gold-layer analytics and BI reporting
07 · AI
RAG PDF Question Answering
An AI-powered Retrieval-Augmented Generation application that allows users to ask questions about PDF documents and retrieve relevant information from the documents.
- Python
- RAG
- LLM
- Embeddings
- Vector Search
- PDF Processing
Key work
- Document loading and chunking
- Embeddings and vector search
- Retrieval and LLM response generation
05 — Workflow
Data analytics workflow
The path I follow from raw inputs to a report someone can use.
- 01Data Collection
- 02Data Cleaning
- 03Exploratory Data Analysis
- 04Statistical Analysis
- 05Visualization
- 06Business Insights
- 07Dashboard / Report
06 — Capabilities
What I can do
01
Data Analysis
Clean, transform, analyze, and interpret datasets.
02
SQL
Write queries using joins, aggregations, subqueries, CTEs, and window functions.
03
Python
Use Pandas, NumPy, Matplotlib, Seaborn, and Python for data analysis.
04
Power BI
Build interactive dashboards, KPIs, reports, and business visualizations.
05
Statistics
Apply descriptive statistics and statistical concepts to analyze data.
06
Cloud
Build practical AWS solutions using S3, Lambda, RDS, EC2, VPC, IAM, and CloudWatch.
07
Data Pipelines
Understand and implement ETL/ELT workflows and Bronze-Silver-Gold architectures.
07 — Learning
Certifications and learning
Areas I am studying alongside project work. Completed certificates will be listed here with the issuer and date.
- Data Analytics
- Python for Data Analysis
- SQL
- Power BI
- AWS Cloud
- Data Engineering
- RAG / Generative AI
08 — Resume
Download my resume
Interested in my background and projects? Download my resume to learn more about my education, technical skills, projects, and experience.
09 — Connect
GitHub and LinkedIn
GitHub
Code and notebooks
Explore my projects, notebooks, SQL practice, Python code, and data analytics work.
Professional profile
Connect with me and follow my journey in Data Analytics, Cloud, Data Engineering, and AI.
10 — Contact
Let's connect
I am open to opportunities in Data Analytics, Business Intelligence, Data Engineering, and related entry-level roles.
- Email: hareram2011000@gmail.com
- GitHub: github.com/hareram08
- LinkedIn: linkedin.com/in/hare-ram-1b5526421