Woman entering data into a computer.
There is a data warehouse integration aspect associated with all business intelligence projects. A data warehouse is an autonomous system that stores electronic data. Specially designed software is used to access the data for the sole purpose of analysis and reporting. There is no mechanism to create, modify, or delete data in the warehouse. Instead, the only options are to write queries, create new reports, and look for trends.
The skills required to achieve any of the data warehouse integration methods include advanced data management, information system skills, and programming.
There are two options for data warehouse integration: full and data only. Tight integration is a system design model 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 is commonly found in large organizations with dedicated staff.
In the full integration model, the data warehouse accesses data stored in the transactional database. This type of architecture reduces storage capacity requirements as the warehouse tools are accessing the original data source directly. However, there are additional risks with this type of architecture. There is no opportunity 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 store 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 a web-based tool for reporting and metrics.
The skills needed to achieve any of the data warehouse integration methods include advanced data management, information system skills, and programming. In-depth knowledge and experience of the systems that will be integrated into the data warehouse is required, as is a fundamental understanding of data management techniques. Most people working in this field have advanced degrees in information technology, mathematics or statistics. In addition to formal education, experience in developing business intelligence tools and implementing this type of technology is a fundamental requirement.
Benefits of data warehouse integration include improved reporting capabilities, the ability to review data in a new way, and a new view of 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 team members need to be trained in this technology to be able to realize any of these potential benefits.