A practical ETL application for these two datasets could involve combining the information from both datasets to gain insights into the relationship between car manufacturer country of origin and car thefts in the US. This could be done by performing a join operation on the two datasets based on the car manufacturer name. Once the data is combined, various analyses could be performed such as calculating the percentage of car thefts for each manufacturer or grouping manufacturers by country of origin to see if thefts are more likely to occur for cars made in certain countries. The resulting insights could be used to inform policy decisions or aid in the development of new security features for cars.
-
Notifications
You must be signed in to change notification settings - Fork 0
Two datasets first one represent the car theft happened in the US, each row in the dataset represents a the number of thefts happened to a car model (made by a car manufacturer) Also attached another dataset of different car manufacturer with their country of origin
GhaidaaShtayeh/Practical-ETL-application
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
Two datasets first one represent the car theft happened in the US, each row in the dataset represents a the number of thefts happened to a car model (made by a car manufacturer) Also attached another dataset of different car manufacturer with their country of origin
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published