Raw Authentic Data Product Build

This is a continuation of the topic that I am striving to cover - Raw Authentic Data Product Build

A bit late to this, but as discussed we need to unpack the "Consumer data model" to build consumer data products.

If you haven't checked my previous posts which covered the authenticity of data products and what should it entail, here are the links

• Raw authentic data product build - 1
• Raw authentic data product build - 2

Consumer Data Products are becoming an essential tool for gaining insights into customer behavior and preferences.

?? ??... Let's understand this with the example of this restaurant, where data products can help restaurants provide better customer experiences.

? ... To build a successful consumer data product for a restaurant, it's crucial to have a strong understanding of both the business objectives and the needs of the customers.

? ... A key part of this is building a robust data model that represents the data being used in the product.

Based on the aforementioned example, I have identified several entities that are relevant to a restaurant's data model, including

• Customers
• Orders
• Menu Items
• Tables
• Reservations

These entities are all interconnected, forming relationships that are critical to understanding the data.

Here's an illustration of the data model:

Customer Table
---------------
customer_id (PK)
first_name
last_name
email
phone

Reservation Table
-----------------
reservation_id (PK)
reservation_date
reservation_time
num_guests
special_requests
customer_id (FK)


Table Table
-----------
table_id (PK)
table_number
max_capacity


Reservation_Table Table
------------------------
reservation_id (PK) (FK)
table_id (PK) (FK)


Menu Item Table
---------------
menu_item_id (PK)
menu_item_name
menu_item_description
menu_item_price


Order Table
-----------
order_id (PK)
order_date
order_time
quantity
menu_item_id (FK)
reservation_id (FK)        

As you can see,

• The Customer entity has a one-to-many relationship with both Orders and Reservations, indicating that a customer can have multiple orders and reservations.
• The Order entity has a many-to-one relationship with both Menu Items and Table Table, indicating that an order can have multiple menu items and be associated with a single table.
• Finally, the Reservation entity has a one-to-one relationship with BookingTables, indicating that a reservation is associated with a single BookingTable.

How a data model helps to realize any business use case is still can't be understood by just drawing up a relationship between entities (Right ?). Therefore an illustration of data flow across different entities can be seen in below diagram

To build a data product based on this data model, it's essential to have a robust data architecture that can handle the different data objects and sources. One Important component of that architecture is the "Data Contract"

Data contracts are essential to building data products. They help to define the data elements, their structure, and their relationships.

A data contract is essentially an agreement between two parties about the data being exchanged.

In the context of building a data product, data contracts can help to ensure that the data being used is accurate, reliable, and relevant to the business objectives.

A well-defined data contract can also help to minimize the risk of miscommunication and misunderstandings between different teams working on the project.

Since a data model implementation at a high level can be seen in this article but we continue to explore "Data Contracts" in the next post.

Do leave your comments below as felt appropriate :)