You work for a dating app company. Your goal is to analyze user behavior, preferences, and engagement patterns to provide insights into matching efficiency and user satisfaction.
Instructions:
Connect the data: Examine the datasets provided, identify relationships, and clean/transform the data as needed.
Analyze and extract insights: Generate new metrics to better understand user engagement and preferences.
Visualize the insights: Use Tableau (or your tool of choice) to create a dashboard showing meaningful insights. (can also be theoretical and explain how you would create it)
Datasets (100 Rows Each)
Please see the csv folder for the files
Table examples and layout
User Data
UserID
Name
Age
Gender
Location
Interests
PremiumUser
SwipesLeft
SwipesRight
1
Alex Johnson
25
Male
New York
Movies, Hiking
Yes
120
80
2
Sara Smith
30
Female
Los Angeles
Cooking, Travel
No
100
50
...
...
...
...
...
...
...
...
...
Match Data
MatchID
UserID1
UserID2
MatchDate
MatchedOn
MessagesExchanged
DateScheduled
1
1
3
2024-01-10
Hiking
10
2024-01-15
2
2
4
2024-01-12
Travel
15
2024-01-20
...
...
...
...
...
...
...
Geographical Data
LocationID
City
Region
AvgAge
AvgIncome
ActiveUsers
1
New York
Northeast
27
75000
1200
2
Los Angeles
West Coast
29
85000
900
...
...
...
...
...
...
Subscription Data
SubscriptionID
UserID
StartDate
EndDate
PlanType
MonthlyCost
1
1
2024-01-01
2024-12-31
Premium
20
2
3
2024-02-01
2024-05-01
Standard
10
...
...
...
...
...
...
Survey Data
UserID
SatisfactionScore
Feedback
RecommendToFriend
1
8
Matches are relevant, premium worth it
Yes
2
6
Too few matches in my area
No
...
...
...
...
Task
1. Data Cleaning & Transformation
Identify and resolve missing or inconsistent data.
Combine datasets (e.g., join matches with users and subscription data).