What is the life cycle of the data warehouse?

The

data warehouse life cycle concerns the constantly changing process that data and archived data have been going through computer storage since the data is created and stored until it is no longer needed and archived in the company's records. The data cycle system of the data warehouse includes the creation of an efficient storage and loading system. Time has shown that simply storing data in a huge computer storage does not work. Instead, it is best to create a storage system, test it and change it as needed to suit the constantly changing data needs of the company. Each book had a card arranged in alphabetical order, allowing visitors to find a book they were looking for. As the library collection has expanded, more cards had to be added and changes were made to make the cards better organized and adapt to their growing size. The same princtly is used because the life cycle of the data warehouse starts again and into existing VIMultiple data must be added.

First in the life cycle of the data warehouse comes the need for the data itself. This desire to easily approach data creates demand in the company to store these data in a way that allows quick access, regardless of whether the data is new or old. The design stage is therefore in the first place. This is a rough phase of development, because designers often have only a vague idea of ​​what types and how much data the system must handle.

Another comes prototype and phase of testing. The working model of some or all data is created and tested by a limited group. When there are problems, reports are reported to programmers who correct the error and update the prototype model. Once the model is ready for larger testing, it enters the operating phase and everyone can use new data warehouses.

Finally, programmers work on repairing any criminalInch that appear after the software function. Although the person has programmed a perfect data warehouse system, it would still have to update it on how it expands and changes the life cycle of the data warehouse. Changes in the system are constantly made to ensure that it works properly and is as simple as possible.