The project involves identifying which factors predict future user
adoption where an "adopted user" is defined as a user who has logged into the product on
three separate days in at least one sevenday period.

The data is available as two attached CSV files:
takehome_user_engagement.csv
takehome_users.csv
The data has the following two tables:

1] A user table ( "takehome_users" ) with data on 12,000 users who signed up for the\
product in the last two years. This table includes:

● name: the user's name
● object_id: the user's id
● email: email address
● creation_source: how their account was created. This takes on one of 5 values:
--------PERSONAL_PROJECTS: invited to join another user's personal workspace
--------GUEST_INVITE: invited to an organization as a guest (limited permissions)
--------ORG_INVITE: invited to an organization (as a full member)
--------SIGNUP: signed up via the website
--------SIGNUP_GOOGLE_AUTH: signed up using Google Authentication (using a Google emailaccount for their login id)

● creation_time: when they created their account
● last_session_creation_time: unix timestamp of last login
● opted_in_to_mailing_list: whether they have opted into receiving marketing emails
● enabled_for_marketing_drip: whether they are on the regular marketing email drip
● org_id: the organization (group of users) they belong to
● invited_by_user_id: which user invited them to join (if applicable).\

2] A usage summary table ( "takehome_user_engagement" ) that has a row for each day that a user logged into the product.