THE PROJECTS below contain aspects of both data and software engineering. Data engineering in terms of designing or building systems for collecting, storing, And manipulation for analysis. Software engineering in terms of both front-end and back-end development.
Big Data Cloud Service Tutorial
Summary
This project is a simple tutorial on how a company might utilize Google's cloud platform. Written in R and published as HTML in markdown, this writeup allows users to see how a data science project comes together from start to finish. Features include utilizing cloud to store and retrieve data, run query on the data using SQL, processing data for mining, applying machine learning algorithms for predictive analytics, visualizing, and analysis.
Tags: R, SQL, HTML, GOOGLE cloud, big data, neural networks, decision tree, naive Bayes, visualizations, normalization.
USER Engagement Analysis
SUMMARY
This Tableau dashboard was created to demonstrate the trending of a website after a new advertisement campaign was launched. The data was created from scratch in python, uploaded to AWS s3, and then connected to Tableau through AWS Athena. The dashboard demonstrates a real-world example of how a company may track marketing success with the use of testing and visuals for engagement variables like number of Users in a day, time spent engaging, ads viewed, pages viewed, and number of clicks. Initially the test results were calculated with an R script, but Tableau Public is not script friendly.
TAGS: Python, R, AWS S3, AWS Athena, TABLEAU, USER ENGAGEMENT, Trending, Linear Regression, and Hypothesis testing.
OUT-OF-STATE MOVING TOOL
Summary
I wanted to build the perfect tool for examining states as a whole and get the most insight as to which areas are a good fit for me. I could not find the perfect data set that fit my needs for this project, so I decided to build it myself from scratch using several sources via web scraping and API. You can explore the map to adjust variables and set ranges you feel comfortable with, resulting in the highlighted states that are the best fit for you. Project Features Tableau dashboard, shiny application, and a write-up of cleaning and analyzing the data. The Tableau Tool can be viewed below.
Tags: R, HTML, DATA Collection, shiny, Tableau, dashboard, API, web scraping, data cleaning.
Google Store Application Analysis
Summary
The goal of the project was to explore the Google Store data and discover the types of apps that bring in the most revenue. This would be beneficial if you are a tech company that wants to explore establishing new applications for a new stream of revenue. In this project, I demonstrated several features that often come up on data science projects including working with unstructured/missing data, establish/build a server to host a database, and run query language for analysis. My results showed that "Get Rich" apps returned the most money, while lifestyle, finance, and family categories typically were the most successful.
Tags: R, product development, business analysis, data mining, SQLite, database development, and query language.