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short data mining exercice

WHAT TO DO:

* You'll find below several files that contain everything you need to answer the questions. You do not need any other data than what is available in these files

* You are free to choose whichever analytical tools you're most familiar with to do this homework. You are free to code in any programming language

* There is a data dictionary to guide you through the datasets. You'll also find a Glossary that defines key words and KPIs in our analytical team

QUESTIONS:

* Unless otherwise mentioned, all the data you need to answer the following questions is in the [url removed, login to view] file

* Q1) What is the difference in success rate between drivers with and without a profile picture?

* Q2) What would be the uplift in success rate for all drivers if every new driver had a profile picture? From now on, you can consider that every other factor impacting success stays constant

* The feature has been implemented as a test on the web desktop only. You have implemented some tracking in the product to know how many users are actually using it. This data has been stored in the [url removed, login to view] file. It collects data on all platforms

* Q3) Considering this evidence, what would be the actual uplift in success rate for drivers publishing their trips on the app?

DATA DICTIONARY:

* driver_id: unique identifier for a driver

* trip_id: unique identifier for a trip made by a driver

* trip_date: date a trip would start

* publication_site_id: medium used to create a trip (web 1056, web mobile 2013, app 5056)

* seat_offered_count: number of seats offered by a driver for a trip

* confirmed_seat_count: number of seats travelled by passenger on a trip

* city_from_id: unique identifier of a departure city

* city_to_id: unique identifier of an arrival city

* city_from_population: population of a departure city

* city_to_population: population of an arrival city

* first_publication_date: date when a driver created her very first trip on 'private car'

* profile_picture_added_date: date when a driver uploaded a picture into his 'private car'profile

Kemahiran: Perlombongan Data, SQL

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Tentang Majikan:
( 0 ulasan ) Romania

ID Projek: #10118112

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Softeria

I have done MS Software Engineering. I had a course on DATA ENINEERING and Artificial Intelligence . I know all data mining techniques (Predication & Classification) and data analysis techniques. I have worked on K-mea Lagi

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I know most of what you want in the messages you leave. But if I do this work I want to know more information so that I can finish it better.

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