Data Warehouses At a Glance
Data warehouses have played an important role in information technology since the 1990s. They are tools that allow organizations to use relevant information to make important business decisions.
While data warehouses were originally only used by large companies, the decreasing cost of computing has allowed them to be adapted by smaller companies. To understand data warehouses, it is important to learn about the data warehouse architecture.
Data warehouses are computerized systems that store information. They information will almost always come from another source. These sources could be programs or applications. Not only is the data warehouse able to store information, it can also analyze that information as well. This is what separates a data warehouse from being a mere computer storage device. Managers can search through the warehouse looking for specific information. Data mining programs can be initiated, and they will look through the data warehouse for patterns or relationships that can help companies make important marketing decisions.
A data warehouse is basically a database that can answer certain questions. They are subject oriented, and they will analyze information and can help managers solve problems. There are a number of steps that are involved with building a data warehouse. These procedures are similar to those that would be used to build other computer programs. The users of the data warehouse must play a role in its construction. The user is important because they are the people who will be using the tools. Each data warehouse is different, and it must be designed in a way that will allow it to meet the needs of those who use it.
The users will decide what type of information will be placed in the warehouse. Once the requirements for the data warehouse have been developed, the elements must be placed in a conceptual model. This will act as a diagram that will be used to build the actual database. At this point, there are a large number of decisions which need to be made about the design and implementation of the warehouse. Once the warehouse has been built, the data must be acquired and stored. It is up to the data warehouse managers to decide what information must be stored in the database. Much of this data will be related to the organization that owns the data warehouse.
However, some of the data may be taken from other sources. An extraction application must be created in order to pull data from other sources to be placed in the data warehouse. The sources must be identified, and some of these will be file, legacy systems, or other databases. The information will be copied into what is called a staging area. Once the data is placed in the staging area, it will need to be cleaned. Once it is clean and free of errors, it will then be copied into the warehouse. It is crucially important to make sure the data is moved into the warehouse correctly. It is not, the project will not be successful.
Metadata is another important concept that is connected to data warehouses. In fact, high quality meta data is important for the function of the database. Metadata is information about information. It is used in the information collection process, and it is also used when the data is accessed or transformed. In the acquisition phase, the information will be mapped and transferred from the operational system. I will provide a large amount of information about the data, and some of this includes updates or algorithms. Data marts are also important. While managers will want to keep them updated, they don’t need to be updated in real time. Data marts are small in comparison to data warehouses and are only hold information about departments that exist within an organization.
Many companies have begin combining a number of small data marts in order create a data warehouse. However, this has led to controversy. Some feel that data marts where never designed to function as data warehouses, and they should not be used for this purpose. It is best to use data marts as a component to a data warehouse instead of a standalone entity. Security is an important issue with data warehouses, and the information must be protected.
