Data warehouse integration is crucial in business intelligence projects. There are two options: full integration, which is commonly found in ERP systems, and data-only integration, which requires a special data extraction tool. Both methods require advanced data management skills and offer benefits such as advanced reporting capabilities and new insights into transactional data. Staff members must be trained in this technology to realize its benefits.
There is an aspect of data warehouse integration associated with all business intelligence projects. A data warehouse is a self-contained system that stores electronic data. Specially designed software is used to access data for analysis and reporting purposes only. There is no mechanism to create, modify or delete data in the warehouse. Instead, your only options are to write queries, create new reports, and look for trends.
There are two options for data warehouse integration: full and data only. Full integration is a system design pattern where the data warehouse is integrated into the primary transactional system. This integration model is commonly found in the latest versions of most enterprise resource planning (ERP) systems. The hardware and infrastructure required to support this type of system is substantial and commonly found in large organizations with dedicated staff.
In the fully integrated model, the data warehouse accesses the data stored in the transactional database. This type of architecture reduces storage capacity requirements as warehouse tools directly access the original data source. However, there are additional risks with this type of architecture. It is not possible to normalize the data for reporting purposes, creating more restrictions on data entry.
In the data-only data warehouse integration model, a special data extraction tool is used to identify the required information, normalize and archive the data in the data warehouse. It is important to understand that this type of data must be stored in another database, requiring the purchase of additional storage capacity. The data warehouse can then be integrated with other tools and applications. It is increasingly popular to leverage a data warehouse into an internet-based tool for reporting and metrics.
The skills required to achieve both methods of data warehouse integration include advanced data management, information system skills, and programming. In-depth knowledge and background in the systems that will be integrated with the data warehouse is required, as well as a fundamental understanding of data management techniques. Most people who work in this field have a master’s degree in computer science, mathematics or statistics. In addition to formal education, experience developing business intelligence tools and implementing this type of technology is a key requirement.
The benefits of data warehouse integration include advanced reporting capabilities, the ability to review data in a new way, and new insights into transactional data. This information can be used to influence decision making, define new business strategies and create new priorities for the organization. It is important to note that staff members must be trained in this technology to be able to realize any of these possible benefits.
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