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Business Requirements for Data Warehouse - Research Paper Example

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It cannot meet their current expectations as an organization because of their limiting goals the organization set out. Their vision was only to…
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Business Requirements for Data Warehouse
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Business Requirements for Data Warehousing Overview of the current data warehouse and business intelligence at Canadian Tire The current BI and data warehouse at the Canadian Tire was started in 1994 and thereafter, it has been on continuous amendments. It cannot meet their current expectations as an organization because of their limiting goals the organization set out. Their vision was only to provide right information/ data at the right for the right decisions, paving way for the proactive and correct business decisions. Canadian Tire principles limited its expansion by being organization centered rather than customer centered.
Requested project team members and their roles
i. CIO and Executive Management: who will justify required cost and come up BI systems using data warehouse technology for the competitive advantages in the available marketplaces.
ii. Project Managers and Decision Support System Architects: they will create accurate organization’s project plans, define requirements that may deter scope creep, and construct an architecture that will meet the organization’s requirements in terms of extendibility, robustness and flexibility over a long period of time.
iii. Database designers: to identify any necessary business data to be store in the physical data model for the data warehouse to make available value to its end users.
iv. Lead designers and business analysts to design the organization’s attainable requirements for data warehouse.
Requirements for the data warehouse and business intelligence.
These will involve:
i. Development roles in company’s decision support and data warehousing system
ii. Pros and cons of the discovery technique and methods for using each of them on data warehouse or any other information decision support system project.
iii. The types of requirements and their advantages in the organization’s development process
iv. Effective against poor requirements at various categories
Lessons learnt about trends and best practices
Trends and best practices enlightens on the understanding of how to define requirements that results to positive ROI; identification of challenges that come with the implementation of a data warehouse; learning of the complete lifecycle criteria in the implementation of a BI system using the data warehouse technology; and to understand how to build a comprehensive data warehouse which is allows for expansions.
A model of the future architecture
Supporting infrastructure changes
The identified infrastructural changes will enable the organization to grow robustly because of effective management and decision making process. Good customer relations will also be ensured, hence giving advantage to the company in terms of market completion.
Summary in support of the design
The effectiveness of the future architecture will enable the organization to overcome the failures that were being experienced in the old design. For instance, the newly designed data warehouse will maintain a copy of data from any source transaction systems. This architectural advancement will provide the opportunity to:
i. Keep track records of all information even when source transactions’ systems do not.
ii. Improve value to operational business features/ applications, i.e. customer relationship management.
iii. Consistently present the organization’s information hence avoiding data duplication.
iv. Reorganize all information in a manner that they make sense to the business users
v. Enhance data quality by ensuring follow of codes and descriptions, flagging and further updating record through spell-check and correction techniques.
vi. Provide a uniform data model for all data of interest in spite of their sources.
vii. Reorganize the data to make sure that it delivers high quality query performance regardless of complexities of analytic queries, with no impact on the operating systems.
References
List, B., Schiefer, J., Tjoa, A M. (2000). Use Case Driven Requirements Analysis for Data Warehouse Systems, Data Warehousing. Friedrichshafen.
Gotel, O. and Finkelstein, A. (1994). An Analysis of the Requirements Traceability Problem, First International Conference on Requirements Engineering. Los Alamitos: IEEE. Read More
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