Parking Space - Data Modelling

Published: None

Source: https://www.linkedin.com/pulse/parking-space-data-modelling-arabinda-mohapatra-debac?trackingId=ux5WBiGsSi2CFJi4kUVf3A%3D%3D

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Parking Space - Data Modelling

Arabinda Mohapatra

Running Kafka streams after dark, diving into genetic code by daylight, and wrestling with Databricks and Tableflow in every spare moment—sleep is optional

September 23, 2024

Designing a Data Model for Parking Space

Fact_Parking_Transaction (Center Fact Table)

• Transaction_ID (PK)
• DateTime_ID (FK) -> Connects to Dim_DateTime
• Vehicle_ID (FK) -> Connects to Dim_Vehicle
• Location_ID (FK) -> Connects to Dim_Parking_Location
• Entry_Time_ID (FK) -> Connects to Dim_Time
• Exit_Time_ID (FK) -> Connects to Dim_Time
• Parking_Type_ID (FK) -> Connects to Dim_Parking_Type
• Rate_ID (FK) -> Connects to Dim_Rate

 Dim_DateTime (Dimension Table)

• DateTime_ID (PK)
• Full_DateTime, Date, Time, Day, Month, Year, Hour, Minute, Second

 Dim_Vehicle (Dimension Table)

• Vehicle_ID (PK)
• Vehicle_Type, Vehicle_Make, Vehicle_Model, License_Plate, Owner_Name, Contact_Number, Owner_Address

 Dim_Parking_Location (Dimension Table)

• Location_ID (PK)
• Location_Name, Location_Type, City, State, Zip_Code

 Dim_Parking_Type (Dimension Table)

• Parking_Type_ID (PK)
• Parking_Type_Description

 Dim_Rate (Dimension Table)

• Rate_ID (PK)
• Vehicle_Type, Parking_Location_ID (FK), Hourly_Rate