The Implementation Process
Planning: Effective planning is paramount to the success of a Business Intelligence and Data Warehousing project. It involves understanding the organization’s current state, identifying areas where improvements can be made, and setting goals and objectives. This step also includes assessing the resources, technology, and personnel needed to complete the project and creating a timeline for its completion. Planning also consists of determining which data sources must be accessed and used in the project and identifying which data mining will be used. Finally, a budget must be set to ensure the project is feasible and cost-effective.
Data Collection: The data collection step is gathering data from the organization’s various sources and analyzing it to uncover trends, correlations, and insights that can be used to make better decisions. This can be done through manual data extraction or automated tools such as web scraping, API calls, etc. During this step, organizations should consider the data’s quality, the information’s accuracy, and the cost of collecting it.
System Design: An effective system design is needed to ensure the BI and Data Warehousing system meets the organization’s goals and objectives. This involves designing the database structure, data architecture, and application interfaces to ensure scalability, data security, and accessibility. This step is also important for identifying data integrity issues and ensuring the system can integrate with other business applications.
Implementation: After completing the system design and data collection, it is time to begin the implementation of the system. This involves setting up the data warehouse and building the data models, reports, and dashboards. The implementation phase also requires the integration of existing business applications with the new system. This step is necessary to ensure users can access the new system and use its benefits.
Testing and QA: Testing and verifying the system’s performance is a key step in the project’s implementation process. This phase involves testing the system to identify potential issues or problems. It is also important to get user feedback to identify areas where improvements can be made. Finally, the system must be tested and monitored to perform as desired.
Deployment: The new Business Intelligence and Data Warehousing system can be deployed after completing the previous steps. This involves launching the system in a production environment and incorporating necessary changes to ensure a smooth user experience. This step also consists of setting up backup and disaster recovery systems to protect data in case of system failure. Finally, the deployment phase requires adequate training for the end users to use the system to its fullest potential.
Jiang, L., & Huang, T. (2020). Business Intelligence and Data Warehousing: Concepts, Methodologies, Tools, and Applications. IGI Global.
Kozielski, S. (2020). Business Intelligence with Data Warehousing. Apress.
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