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...
Miller Inc. is a company that wishes to develop a new and more efficicent data repository for all data collected, stored, and transferred. Their desire to create a data warehouse that operates quickly with less effort is the purpose of this project. Adaptation of database modeling along with designing their data warehouse will lead to higher consumer and employee satisfaction. The project goal is to create a database schema to
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