Business Requirements Document
Miller Inc. looks forward to creating a data repository for all data collected that is beyond the current relational database it currently uses. The company has currently outgrown the relational database in Oracle that it currently uses. Though it enables data to be stored in different tables that can be linked together using record keys, the amount of keys and records makes it difficult to operate a standard relational database. The company thus needs to adapt database modeling in designing their data warehouse. This is the project. Data modeling extends the online transaction processing models that are common in relational database into data warehousing. The project goal is to develop an appropriate database schema to be designed alongside other components such as identifying metadata. The IT role is to model the data warehouse, implement and test it.
Scope
Scope of the project
The scope of the project is to identify and gather database requirements, design the dimensional model, develop the system architecture, design the relational database and online transactional processing model, develop the data maintenance application, develop analysis applications to test and deploy the system Hughes, 2008()
Applications
In order to meet the target production date, only these applications will be implemented: loading, indexing and summarizing tables, scanning, joining, sorting, aggregating and fetching data. These are deemed to be most relevant to the system needed by Miller Inc. In handling all its data-intensive tasks.
Sites
These sites are considered part of the implementation: testing, live testing, production and backup sites. The testing site will be used for testing applications that are still in the development phase. After testing in the testing site, the live testing site will be used to test the application on a few records in real time to check how it handles live data. The production site will be most important since it will be the one that is used by consumers. The last site is the backup site that will be used to store data backups.
Process re-engineering
The ETL (extract, transform and load) functions will be used to re-engineer the processes used in the relational database. This involves extracting data from all the disparate sources such as the relational database and XML files, transforming it to conform to the schema of the developed data warehouse through removing duplicates, deriving calculated values, generating keys, validating and cleaning the data and then lastly loading it to the data warehouse Humphries, Hawkins, & Dy, 1999()
Customization
Customizations will be limited to calculated data values. This will be done so to minimize the amount of metadata that the system will have as well as ensuring that the system is scalable to include other forms of data that the organization may want to collect and analyze in the future.
Interfaces
The interfaces included are customer, analysts and administrator interfaces. These will all be accessible through web-based applications and will be built entirely in a custom fashion to ensure the organization's data is secure. The customer interface will allow them to view trend data for their websites while the analysts interface will allow them to access all customer data in an anonymous fashion in order to conduct further analyses. The administrator interface will be used to administer the warehouse and the system in general.
Architecture
Before the data warehouse is implemented in full scale, application and technical architecture will be three-layer architecture that is the source, reconciled and data warehouse layer. These will be repopulated through the ETL process earlier described and ensures that the data warehouse works in the best way possible. However, with time, the single-layer architecture will be used to ensure there is minimal redundancy in the system and thus reduce size of data being stored.
Conversion
All data in the relational database will be considered for conversion to the data warehouse schema through the ETL process.
Testing
Four testing engagements will be incorporated. First is new data warehouse testing where the data warehouse will be testing as it is being build using ETL tools. Second, as the data is being migrated, the data warehouse will be tested. Third is change request testing whereby the data warehouse will be tested to meet the needs of the organization and last is report testing where the end result of the data warehouse is tested to validate its layout, the data and, calculations.
Funding
The project is 100% funded by Miller Inc. And funding supports all aspects of development, implementation and testing of the data warehouse.
Training
All members of staff will be trained on the new data warehouse despite their status in the organization. However, different levels of testing will be implemented for different categories of staff. This will ensure that they are aware that the company is using a new data management system and that they understand what the change involves.
Constraints and assumptions
The following constraints have been identified: unique constraints where data in a particular column are not unique and foreign-key constraints where two keys share a primary key-foreign key relationship. The following assumptions have been made in defining the scope, objectives and approach. First is that the data models that underline the services will not support efficient queries that are required to join many concepts together. The second is that the organization will be able to reuse some of the solutions it has such as interfaces. Third is that the data warehouse can be adapted without redesigning or developing new services for consumers.
Risks
One of them major risks that is identified is that the data from the relational database may be too big to be cleaned with ease. Second is that the new technology will not be well understood by all members of staff. A third risk is that the company may have set unrealistic schedules that lead to the project being poorly architected.
Scope control
The scope of the project will be controlled by identifying a representative of the management to manage change control. This individual will also be responsible for any changes that affect the timeline or costs of the project.
Relationship to other systems
The project management team will be responsible for informing the IT department and...
The only known business initiative is consumer product offering.
Resource
The data warehouse may need to be offshored or outsourced in order to keep running costs low and to reduce or mitigate risk associated with data warehouse management. The organization may also need to increase its staff base in order to have more knowledgeable personnel to manage the data warehouse.
Task
Person in-charge
Time
Planning
Prepare project goals and objectives
Project manager, IT staff
1-week
Review project goals and objectives
Project manager, IT staff
2 days
Review and recap proposals and contracts
Project manager
3 days
Assess opportunities and risks
Project manager
2 days
Identify constraints and other obstacles
Project manager, IT staff
3 days
Identify required nonhuman resources
Project manager
2 days
Review scope of project
Project manager
2 days
Identify the procedure for monitoring and evaluation of the project
Project manager
1 day
Project high-level scope of the project
Project manager
2 days
Assemble core project team
Identify required skills from organization
Project manager
2 days
Identify required skills from other project stakeholders e.g. IBM who are the owners of Oracle
Project manager
3 days
Analyze availability of staff
Project manager, administrator
2 days
Nominate project team members
Project manager
1 day
Review team member's availability
Project manager
1 day
Team members accept responsibility
Project manager, all team members
1 day
Analysis
Analyze and design the project organizational units
Project manager, administrator
2 days
Analyze organizational roles
Project manager
2 days
Analyze stakeholder relationships and roles
Project manager
3 days
Analyze and design network identify policies
Project manager, all team members
2 days
Analyze and design policies and workflows for provisioning
Project manager, administrator
3 days
Analyze and design high level methods for importing data
Project manager
2 days
Analyze software and hardware architecture
Project manager
2 days
Design
Review project goals and objectives with team members
Project manager, all team members
2 days
Develop project plan
Project manager, all team members
Identify resources required
Project manager, all team members
2 days
Review project plan with identified resources
Project manager, all team members
3 days
Design test strategy
Project manager, all team members
1 day
Project communication
Develop communication plan
Project manager, all team members
1 day
Identify and publish project updates
Project manager, all team members
1 day
Publish problems for issue tracking
Project manager, all team members
1 day
Publish scope control instruction
Project manager, all team members
1 day
Publish schedules of the team and team members
Project manager, all team members
1 day
Develop team status reporting rules
Project manager, all team members
1 day
Identify and publish functional responsibility of team members
Project manager, all team members
1 day
Implementation
Confirm suitability of workspaces
Project manager, all team members
1 day
Confirm stakeholders are on board
Project manager, all team members
1 day
Confirm availability of resources
Project manager, all team members
1 day
Conduct final checks before project starts
Project manager, all team members
1 day
Project implementation
Configure identity policies
Project manager, all team members
1-week
Utilize data import methods
Project manager, all team members
1-week
Full HR data load
Project manager, all team members
1-week
Get access to sample data
Project manager, all team members
1-week
Load test data
Project manager, all team members
1-week
Review results and approve
Project manager, all team members
1-week
Incremental data load
Project manager, all team members
1-week
Obtain schema and layout
Project manager, all team members
1-week
Test provisioning policies
Project manager, all team members
2 weeks
Test manual and automatic data provisioning
Project manager, all team members
2 weeks
Test workflow
Project manager, all team members
2 weeks
Prepare system for production
Verify hardware matches requirements
Project manager, administrator
2 days
Verify network capabilities
Project manager
2 days
Prepare and verify software environment
Project manager
3 days
Validate operating systems
Project manager, all team members
2 days
Verify database engines
Project manager, administrator
3 days
Tune system for performance
Project manager
2 days
Review and…
References
Hughes, R. (2008). Agile Data Warehousing: Delivering World-Class Business Intelligence Systems Using Scrum and Xp. Chicago: iUniverse.com.
Humphries, M., Hawkins, M.W., & Dy, M.C. (1999). Data warehousing: architecture and implementation. Englewood Cliffs: Prentice Hall.
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