The aim of this project was to find mobile apps that are profitable on Apple appstore and Google playstore.
Assumption: The number of users determines revenue for any given app — the more users who see and engage with ads, the better.
The goal was to analyze data to help developers understand what type of apps are likely to attract more users.
I built a PostGres database for storing data related to crimes that occurred in Boston.
This dataset is available in the file boston.csv in the repo.
Performed Exploratory analysis using python to explore hackernews posts data in order to deduce the most effective time to post in other to get more engagements.
Hacker News is a site started by the startup incubator Y Combinator, where user-submitted stories (known as "posts")
are voted and commented upon, similar to reddit.
Analysis was performed on about 300,000 posts using just python and in built libraries
Analysed data using SQL and Pandas to answer business questions. This is a project extracted from the DataQuest: Data Engineer Track.
I used the Chinook database. The Chinook database contains information about a fictional digital music shop - kind of like a mini-iTunes store.
This information is contained in eleven tables in an SQLite database file.
Analyzed CIA World Factbook, a compendium of statistics containing demographic information about all of the countries on Earth
Analyis done using SQL
I have designed some truly breathtaking Power BI dashboards.
Contact me for dashboard links.