kevinndungu-source,Kevin.N,github

Welcome to my GitHub portfolio: a collection of data-driven projects demonstrating my cloud data engineering, data analytics, and business intelligence expertise. Every project demonstrates my commitment to using cutting-edge technology and a strong data infrastructure to create perceptive solutions. Please take a moment to review each project to see the variety of data analytics and engineering talents I possess.

My tools for programming, data manipulation, storage & visualization:-

Python3	Conda	Jupyter	Spark	MySQL	Postgres	SQLserver	AzureSQL	Plotly	Matplotlib

Tools for working with frameworks and main libraries for Python3:-

Numpy	Pandas	Sklearn

Version control, Environment & Testing:-

Git	Docker	Postman

Certifications:-

Kevin.N's Projects

amazon_emr_demonstration_resources

Explore and replicate Amazon EMR (Elastic MapReduce) setup and utilization for big data processing and analytics tasks, featuring comprehensive demonstrations from VPC creation to Spark job execution.

amazon_emr_serverless_demonstration

Explore the capabilities of Amazon EMR Serverless by processing semi-structured review data with Apache Spark, showcasing efficient big data analysis without managing clusters.

amazon_redshift_s3_data_pipeline

This repository contains code and documentation for the Amazon Redshift project, showcasing a data pipeline using Amazon S3. Explore how I manage and analyze large datasets in the cloud!

data_analytics_project

Explore comprehensive retail analysis and insights focusing on Marley International Store, powered by data analytics techniques and visualizations using Python, PowerBI and Jupyter Notebooks.

gcp_bigquery_project

Analyze the Chicago Crime Dataset using SQL queries in Google BigQuery to uncover insights and trends, supporting informed decision-making for law enforcement and community stakeholders.

hands_on_introduction_data_engineering-4395021

This repo is for the Linkedin Learning course: Hands-On Introduction: Data Engineering.

machine_learning

Machine Learning - This is a hands-on Machine Learning endeavor showcasing data preprocessing, feature engineering, and model deployment using Amazon SageMaker, aimed at advancing proficiency in ML workflows.