A ‘data warehouse’ or an ‘enterprise data warehouse’ is a computer-based term that is given to a system. The system is basically used for analysing and reporting data. Data warehouses are central storehouses/ depositories that store data coming from a single or multiple incongruent sources. These warehouses are enterprise strategies that are aimed at solving problems related to fixed data (data silo) or data that is isolated, and which is not accessible and well- integrated to other parts of the firm.
Intrinsically, a data warehouse sets the basis for assisting management, both by looking and observing historical trends and also aiding in predicting the future developments/tendencies.
To be more specific, enterprise data warehouse is a collection of data, as described by Bill Inmon, a recognized computer scientist. Further, he broke down the definition into five types: ‘subject-oriented’, ‘integrated’, ‘time-variant’, ‘non-volatile’.
Generally, a storage place is a place where you keep all the things that have been made use of in the past but are not needed at the present; although might be needed in the future and for this reason, all the data is dumped/deposited in a depository.
Similarly, when an enterprise is running, all the data that is generated cannot be stored on laptop or computer devices because they take up a lot of space. Thus, what organizations or enterprises do is that they transfer all of the data to a warehouse so that they can keep a backup to help them in times of emergency and urgency.
In addition, a data warehouse has more than one use. The use that data warehouse gives is according to the type and collection of data. Like, if one wishes to analyse a subject area like ‘sales’, he/she would need to extract data generated in the past so that it can be compared to the present data in order to provide an analysis. Such type of collection is called ‘subject-oriented’ data.
However, when the data concerns the identification of a certain product or an item; a data warehouse incorporates information from various sources and what it does then is that it identifies it in one way. For example, if source X and Y have varying ways of identifying a product when it reaches the data warehouse, it recognizes both the information in the same manner.
However, a warehouse uses information when historical data is needed. As mentioned earlier, this is when the data is no longer in continuous use but there might be a situation where it might be the case and this is why you go to the warehouse to extract the data and it doesn’t matter how old the data is. For example, if you need to know anything particular about a customer, the data warehouse will have everything related to that customer. So, this way you can get access to it easily. Also, the other thing that is important to highlight is that the data that reaches the data warehouse does not change. For this reason, the data you wish to retrieve will be the original data.