Data Warehouse Management System

This document provides an overview of data warehousing and discusses the system requirements for managing a warehouse of auto parts. It includes diagrams such as a use case diagram, domain model class diagram, and event partition system model. The document concludes with a proposal for a new warehouse management system.

Running head: DATA WAREHOUSING
Data Warehouse Management System
Name of the Student
Name of the University
Author Note

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Table of Contents
Introduction................................................................................................................................2
Data Warehousing......................................................................................................................2
System Requirements.............................................................................................................2
Diagrams................................................................................................................................3
Conclusion..................................................................................................................................6
References:.................................................................................................................................7

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Introduction
Data ware housing is very simplified way managing the data which are not present in
single place (Pang & Chan, 2017). Jack and Daniel are having auto-parts business. They want
to upgrade the current warehouse system for better dynamic results. The intended design of
the system in this report is supposed to fulfil their needs. In the later section of this report, the
functional and non-functional requirements are discussed with the help of use case, domain
model class diagram and event wise partitioned system model.
Data Warehousing
Data warehousing is technique in which data is collected from varied places and
managed to gain efficiency (Cravero, Mazón & Trujillo, 2013). According to the current
scenario of Jack and Daniel, the analysis of requirements is needed to be done. Then the
design comes in play where this system is supposed to deliver tasks like managing and seeing
a warehouse of auto parts with order details, shipment details, documentation and system
status like warnings and stock available.
System Requirements
The requirements for this intended system can be categorized in to two section which
are functional and non-functional requirements. Functional requirements has system tasks to
provide an efficient interface to manage the warehouse of auto parts (Abai, Yahaya &
Deraman, 2013). The inventory is manipulated and analysed by various functions which have
some set of rules. 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. On another hand, non-functional
requirements: The system is designed to give accurate inventory details to user as a real-time
operation (Khouri et al., 2014). The system can add new items in the orders from the

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inventory and provides the stages of order status. The login feature is introduce so no other
person can gain access in the system. The user interface is kept simple so that it won’t take
any time learn and understand the features of it.
Diagrams
Figure 1: Use Case Diagram
Source: created by author
Use cases:
a) Login: login to the system.
b) Order load: checks the order frequency and loads.
c) Orders: managing orders.
d) Processing order: orders which are in processing.

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e) Shipment: tracks the shipment status.
f) Orders packed: checks the order is packed or not.
g) Inventory: access the inventory items.
h) Documentation: checks the documentation process.
i) System alerts: checks the error in the system.
j) Invoice: generate invoices for each order.
k) Crystal reports: generates the crystal report for orders.
Actors:
 User: the person who will use the warehouse.
 Order manager: manages the order packing, order processing order load.
 Document manager: manages the outbound documents and details.
 Inventory manager: manages the main storage (auto parts), system alerts and order
loads.

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Figure 2: Domain Model Class Diagram
Source: created by author
Classes:
i. Orders: keeps the track of order details.
ii. Processing orders: keeps the track of “In processing” orders details from orders.
iii. Packed order: keeps records of packed orders from orders.
iv. Shipment: keeps records of picked up order and ongoing shipment.
v. Inventory: keeps records of all type of auto parts.
vi. Documents: keeps the records of documents for each order.
vii. Invoice: keeps the records of invoices for each order as a document.
viii. Crystal reports: keeps the records of crystal reports for each order as a document.

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Figure 3: Event Partition System Model (Diagram 0)
Source: created by author
Conclusion
Although the system was present for managing data for Jack and Daniel, the proposal
of a new warehouse management system will enhance the performance of the system. In this
development of a data warehouse management system, full efforts have been made according
to the the business requirements. 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. The use case further extended into class and event partitioned model diagram.

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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.
Cravero Leal, A., Mazón, J. N., & Trujillo, J. (2013). A business-oriented approach to data
warehouse development. Ingeniería e Investigación, 33(1), 59-65.
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.
Pang, K. W., & Chan, H. L. (2017). Data mining-based algorithm for storage location
assignment in a randomised warehouse. International Journal of Production
Research, 55(14), 4035-4052.