The google play store is one of the largest and most popular Android app stores. It has an enormous amount of data that can be used to make an optimal model. We have used araw data set of Google Play Store from the Kaggle website.This data set contains 13 different features that can be used for predicting whether an app will be successful or not using different features. This data set is scraped from the Google Play Store. This journal talks about different classifier models that we used for prediction purposes and finding which one gives the highest accuracy. This journal also gives detailed information on feature extraction and the complete Data visualization done on this data set.
https://drive.google.com/file/d/16yxbErCy1LKqk7RFbp-DjZTCbr20bxb2/view
https://public.tableau.com/app/profile/soumit.kar/viz/PlaystoreDashboard1/Dashboard4
Minimize the number of fields.
Minimize the number of records
Optimize extracts to speed up future queries by materializing calculations, removing columns and the use of accelerated views