Foredata is a very new term that stands for "Developed From Fore" meaning beforehand, up front, at or near the front. In fact not many are aware of the existence of such word but the underlying function of the foredata has always been there and has existed as early as the database system has existed years ago. Foredata are all data about the objects and events, including both praedata and paradata.
In a data warehouse implementation, every data that a data consumer interacts with, regardless of whether he is a high ranking official or just a rank and file employee, is foredata.
Foredata are the upfront data which are used for describing a data architecture’s objects and events. They are also used for tracking or managing the said objects and events in the real world as they really represent also these said objects and events.
But foredata are no different from the data inside the data warehouse or from its various data sources. The foredata is only a term to represent the way data are being used although they are structurally the very same data circulating around from one data source to another or the same data being stored in the data warehouse until someone queries them for specific information.
To some degree, a foredata could be considered some kind of a replica of the data which are being used in the backend processing of the system. For instance, as the definition goes that "foredata are the upfront data that an organization sees about objects and events", any report generated by the company’s data consumer are foredata in that their momentary purpose is to present the data and not to be input for a functional backend processing.
Since the term foredata is really very new, there are others from the IT profession who differentiate foredata from the other kinds of data in that foredata refers to the data which is current, revolving and active. This is in contrast to the data warehouse data which are dormant or in some sort of archived state.
Foredata in general refer to the data after the all those disparate data coming from various data sources have already undergone through the process of extract, transform and load (ETL). This is because the raw data before ETL may have come from other sources and they have not yet been stripped or their attached formatting and other information.
Once the data start getting into the first ETL stage which is the extract, the are already stripped to the core. After that they are transformed and this can be done by adding XML tags and other attributes which make them fit into the business rules and data architecture that they are intended to be used.
If we go back to the above definition "Foredata are all data about the objects and events, including both praedata and paradata and they are the upfront data that an organization sees about objects and events", these extracted and transformed data will see fit.
This will also distinguish foredata from all other data within the data warehouse and enterprise information system. As we all know, the other data within the information system are flat files, networking protocol associated data, and multimedia data.
Foredata constitute elements for reporting which is the most essential purpose of a data warehouse. Companies need to make sure that they get the latest trends and patterns so that they can evaluate the efficiency of their business operation strategy and reformulate some policies are revise some product management in order for the company to gain competitive advantage.