Understanding The Data Warehouse
To understand the data warehouse, it is important for you to realize that it is not a single object. It is more of a strategy or a process, an integration of various support systems and programs that are knowledge based. The goal of using a data warehouse is to allow businesses and organizations to make strategic decisions.
The data warehouse is a tool that is designed for the long term. It takes the data from the organization as a whole, and presents it in a way that allows users to use it for a number of different purposes. In most cases, the information obtained from a data warehouse will be used for strategic analysis. Some of the things which it is commonly used for include market research, forecasting, and the identifications of trends.
Data warehouses are specifically designed for business executives and anyone who has the responsibility of making strategic decisions. By using a data warehouse, a company will have access to information that is detailed and consolidated. This information will be taken from various sources, and while some of this information is external, other parts of it are internal. Despite this, many people make the mistake of believing that a data warehouse is merely a tool that is used for collecting data and making reports on it. To run a data warehouse efficiently, the users are expected to have a great deal of technical skill. In addition to this, having business skills are useful as well.
To use a data warehouse, the user must be able to correctly identify the business information that is comprised in it, and they must also be able to set priorities for the information that is stored in the data warehouse. The data within the data warehouse will be broken down into subject areas, and the user must be able handle each of these areas efficiently. It is also important for the data warehouse to be scalable. This scalable structure will play an important role in the foundation of the system, and the proper hardware and software must be implemented. In addition to the data warehouse itself, the maintenance of the data is equally important.
While operational databases played an important role in the past, they are not used directly for information processing within modern data warehouses. In most cases, they will merely act as a repository for data, and they will also play a fundamental role in information processing. There are a number of reasons why a company should want to separate operation data bases from those that are information based. One of the most important reasons for this is because the users of both forms of data are different. While analysts will often be responsible for working with informational data, administrative employees will spend more time working with operational data.
The data must be cleaned and transformed in a way that allows it to remain accurate. The consistency of data within the data warehouse is extremely important. Summarization also plays an important role in the function of the data warehouse, and it is important for the user to make sure the correct level is created, thus allowing the organization to make important business decisions. Another issue with many data warehouses is user friendliness. If the employees have a had time utilizing the capabilities of the data warehouse, this could limit the success of the company. In some cases, data warehouse projects have failed because the tool was not user friendly, and millions of dollars were lost.
Because of the complexities surrounding the data warehouse, the user must be educated in how to efficiently use it. A help desk will generally be of great use, and designing tutorial for the user can be helpful as well. The success of a data warehouse is not just dependent on the tool itself, but it is also dependent on the implementation and how the company educates the employees in using it. Before the introduction of data warehouses, most companies used various databases to store information that was related to transactions, reporting, or other business processing. In addition to this, the technology for both database types are inherently different. The information data is more closely related to historical trends, and this is not a necessity for operational databases.