Question

, Cname, City) ORDER(Order#, Odate, Custw, Ord Amt) ORDER_I… # Consider the following six relations for an order-processing database application in a company: CUSTOMER(Cust#, Cname, City) ORDER(Order#, Odate, Custw, Ord Amt) ORDER_ITEM(Order#, Item#, C2ty) ITEM(Item#, Unicprice) SHIPMENT(Order#, Warehouse#, Ship_date) WAREHousE(Warehouse#, City) Here, Ord_Amt refers to total dollar amount of an order; Odate is the date the order was placed; Ship_date is the date an order is shipped from the warehouse. Assume that an order can be shipped from several warehouses. Specify the foreign keys for this schema, stating any assumptions you make.

Short answer

The foreign keys in this schema are - ORDER_ITEM(Order#, Item#), ORDER (Cust#), and SHIPMENT(Order#, WareHouse#).

Step-by-step solution

Identify primary keys in the tables

To identify foreign keys, we first need to find out the primary keys. Primary keys are those fields which can uniquely identify a record in a table. So, looking at the tables: \n \n CUSTOMER(Cust#), ORDER(Order#), ORDER_ITEM(Order# and Item# combined), ITEM(Item#), SHIPMENT(Order# and Warehouse# combined), WAREHOUSE(Warehouse#) are the primary keys.

Analysing the relationship between tables

Looking at each table, we can assume logical connections between them, by way of customer placing an order, an order involving multiple items, every item having its price and an order being shipped from warehouse. This gives us a basic relationship mapping.

Identify foreign keys

Now, based on the relationship, we can determine the foreign keys. Foreign keys in a table are those which are primary keys in some other table, and they establish a link between these tables. \n \n ORDER_ITEM(Order#, Item#), ORDER (Cust#), and SHIPMENT(Order#, WareHouse#) fields are the foreign keys as they link the various tables together. \n Order# is a foreign key in ORDER_ITEM and SHIPMENT, as Order# is the primary key in ORDER. \n Similarly, Item# is a foreign key in ORDER_ITEM as Item# is the primary key in ITEM. \n Cust# is a foreign key in ORDER as Cust# is primary key in CUSTOMER. \n And Warehouse# is a foreign key in SHIPMENT as Warehouse# is primary key in WAREHOUSE.

Key concepts

Relational Database

A relational database is a digital database based on the relational model of data. This model organizes data into tables (also called relations), where each table consists of rows and columns. Each row, or record, represents a unique data entry, and each column, or field, holds a particular kind of data.

Relational databases allow users to establish connections between these tables through unique keys. These keys can link data across multiple tables, making it easier to query and manipulate large volumes of information efficiently.

• Tables: These are the basic storage units where data is organized in rows and columns.
• Rows: Each row in a table represents a unique entry of data.
• Columns: Columns define the type of data stored in each row.

Through properly designed schemas, relational databases ensure that the data remains organized and the integrity maintained.

Primary and Foreign Keys

Primary and foreign keys are crucial elements in relational databases, enabling the creation of relationships between tables. Understanding these concepts is essential for effective database schema design.

A primary key is a unique identifier for a record in a table. It ensures that each entry is distinct and easily searchable within its table. For example, in the CUSTOMER table, Cust# serves as the primary key ensuring each customer is uniquely identifiable.

• Primary Key: The unique field that identifies each record within its table.

Conversely, a foreign key is used to link records from one table to a primary key in another table, establishing a relationship between them.

Foreign keys ensure referential integrity, meaning a record's relationship to others is maintained even as data changes. For example, Order# in SHIPMENT acts as a foreign key, as it refers back to the primary key Order# in the ORDER table.

• Foreign Key: A field that references a primary key in another table, enabling linked data across tables.

Order Processing Database

An order processing database is a specialized system designed for managing all aspects of an order lifecycle. This type of database typically involves multiple related tables representing different entities and processes within an order management system.

In the example provided, tables like CUSTOMER, ORDER, ORDER_ITEM, ITEM, SHIPMENT, and WAREHOUSE form the schema of an order processing database. Each of these tables plays a distinct role in capturing and managing data that flows through the order system.

• CUSTOMER Table: Holds data about each customer placing orders.
• ORDER Table: Tracks order details including order date and customer involvement.
• ORDER_ITEM Table: Details the specific items involved in each order and their quantities.
• ITEM Table: Contains details about the items available, including pricing.
• SHIPMENT Table: Manages shipment details including from which warehouse items are dispatched.
• WAREHOUSE Table: Stores information about various fulfillment centers from which shipments are sent.

This structured approach allows businesses to maintain efficient, accurate handling of order data from creation to fulfillment.

Data Modeling

Data modeling is the process of creating a visual representation of a database structure to ensure data consistency and system functionality. This involves designing tables, relationships, and keys to accurately represent an organization's data needs.

In the context of an order processing database, data modeling involves mapping out entities such as orders, items, and shipments, and understanding how these entities relate to one another.

Effective data modeling involves:

• Entity Definition: Determining the essential components of a database, such as orders or customers.
• Relationship Mapping: Establishing how different tables interact, typically through keys.
• Constraints Implementation: Adding rules to maintain data integrity, such as primary and foreign keys.

Through comprehensive data modeling, businesses can create robust database schemas that easily adapt to changing data needs while ensuring efficient data retrieval and storage.