For the purpose of this scenario, the information sources are represented by these operational database systems which are actually relational databases, and are required to be integrated in the data warehouse. Every clinic has also a manager and a number of staff, such as, cleaners, nurses, and etc.
Since, data warehouses are capable of handling server tasks connected to querying, therefore, the proposed implementation of data warehouse would support the company’s transactions systems to complete transactions within a desirable time frame by running the reports and queries on a server.
Allow the users (company staff) to obtain reports and make queries efficiently as data warehouse gives the user control over the response time by storing the older data and the recent data in well-organized manner.
Despite the fact that the company can enjoy many benefits from implementing the proposed implementation, there are some major drawbacks as well which are highlighted in another article at Exforsys (The disadvantages of a data warehouse, n.d.):
Since, data warehouse contains historical data about a company’s transactions, the value of this information might be limited because the businesses operating in today’s market are in constant transition, and therefore, it may not be always worthy to use a historical data.
The process of extracting, transforming, and loading data from the source systems in real-time can be one of the most challenging tasks for any data warehouse. The ETL process normally requires downtime of the data warehouse, and therefore, it is usually carried out late at night to avoid any inconvenience because users cannot access data warehouse during the process. However, there can’t be any system downtime when the data is being loaded continuously in real-time. Unfortunately, most of the traditional ETL tools and systems are incapable of supporting continuous updates in the data warehouse without