Detailed Architecture and Design of Auto-Parts Warehouse System Report

This report details the architecture and design of an auto-parts warehouse management system, addressing the need for a more efficient system. The report begins by outlining the functional and non-functional requirements, crucial for the system's operation. It then presents a use case diagram illustrating major use cases and actors involved in the system. A domain model class diagram provides a visual representation of the system's data structure, and finally, an event-partitioned system model is developed to encompass all identified use cases. The report covers order processing, inventory management, and reporting functionalities, providing a comprehensive overview of the proposed data warehousing solution for the auto-parts business.

Running head: DATA WAREHOUSING
Auto-Parts Warehouse Management System
Name of the Student
Name of the University
Author Note

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Table of Contents
Introduction................................................................................................................................2
Discussion..................................................................................................................................2
Requirements..........................................................................................................................2
Diagrams................................................................................................................................3
Conclusion..................................................................................................................................6
References:.................................................................................................................................7

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Introduction
Jack and Daniel are running their auto-parts business. Their need is to change the
current warehouse system into new efficient warehouse management system. This proposed
system can be able to handle the highly dynamic processes for managing the warehouse
(Mundlapudi, Banala & Koneru, 2016). The functional and non-functional requirements are
discussed with the help of use case, domain model class diagram and event wise partitioned
system model (diagram 0).
Discussion
Data warehousing is technique in which data is collected from varied places and
managed to gain efficiency (Vaisman & Zimányi, 2014). From the above mentioned case
study, the proposed model is supposed to perform following functions: fetching all type of
orders, inventory management, order process, order pickup, load management, outbound
documentation, system alerts, packing orders and crystal report generation.
Requirements
The auto-parts data warehouse management system can be developed after defining
the functional and non-functional requirements, discussed below:
 Functional requirements: The system has goals to provide of an efficient interface to
manage the warehouse of auto parts. The management can be done by various
functions (Abai, Yahaya & Deraman, 2013). The system keeps a track of orders, its
processing state, packaging process, order pickup and management of load in orders.
The system can also generate the invoices for the each orders along with the crystal
report.
 Non-functional requirements: The system is designed to give accurate inventory

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details to user as a real-time operation. The system can add new items in the orders
from the inventory and provides the stages of order status (Khouri et al., 2014). The
system have a login feature that will require password. The system can be managed in
such a way that it does not require any additional learning to operate the system.
Diagrams
Figure 1: Use Case Diagram
Source: created by author
Use cases:
1. Order in process: orders which are in processing.
2. Login: login to the system.
3. Orders: managing orders.
4. Order load: checks the order frequency and loads.
5. Pick up: checks the order is picked or not.

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6. Packed orders: checks the order is packed or not.
7. Inventory: access the inventory items.
8. System alerts: checks the error in the system.
9. Crystal reports: generates the crystal report for orders.
10. Invoice: generate invoices for each order.
11. Outbound documentation: checks the documentation process.
Actors:
1. User: manages the warehouse.
2. Outbound manager: manages the outbound documents and details.
3. Inventory manager: manages the inventory items (auto parts), system alerts and order
loads.
4. Order manager: manages the order packing, order processing order load.

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Figure 2: Domain Model Class Diagram
Source: created by author
Classes:
1. Orders: keeps the track of order details.
2. Order in process: keeps the track of “In processing” orders details from orders.
3. Order packed: keeps records of packed orders from orders.
4. Order picked up: keeps records of picked up order.
5. Inventory: keeps records of all type of auto parts.
6. Outbound documents: keeps the records of documents for each order.
7. Crystal reports: keeps the records of crystal reports for each order as a document.
8. Invoice: keeps the records of invoices for each order as a document.
Figure 3: Event Partition System Model (Diagram 0)
Source: created by author

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Conclusion
The proposal focuses on the system development of a data warehouse management
system. The efforts have been made for developing the data warehouse with the business
requirements of Jack Greig and Daniel Cox. The requirements for the development has been
discovered. Later in the proposal, the use case and actors were identified and a use-case
diagram is developed. Along with use-case, the domain model class diagram and event
partitioned system model is also developed.

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References:
Abai, N. H. Z., Yahaya, J. H., & Deraman, A. (2013). User requirement analysis in data warehouse
design: a review. Procedia Technology, 11, 801-806.
Khouri, S., Bellatreche, L., Jean, S., & Ait-Ameur, Y. (2014, October). Requirements driven data
warehouse design: We can go further. In International Symposium On Leveraging
Applications of Formal Methods, Verification and Validation(pp. 588-603). Springer, Berlin,
Heidelberg.
Mundlapudi, B., Banala, K., & Koneru, R. (2016). U.S. Patent No. 9,460,188. Washington, DC: U.S.
Patent and Trademark Office.
Vaisman, A., & Zimányi, E. (2014). Data warehouse systems. Data-Centric Systems and Applications.