An integrated data resource is composed of many different data sources that have been applied with several tools to overcome disparities. For instance, without the aide of integration tools, a business enterprise may have several database systems in each of the departments within the business organizations.

These database systems may be relational in one department and non-relational in another. On one relational database management systems may come one vendor in some departments and in other departments, they may be using RDMS from another vendors.

And in some more cases, some departments may be using flat files or legacy data. With the help of an integration software tool, the problem arising from data disparity will be minimized at least and eliminated at most.

An operational data store is a place or logical area which is basically a database that handles integration of disparate data from multiple sources so that business operations, analysis and reporting can be facilitated while the business operation is progressive.

Since data comes from various disparate sources, data integration at this data store are being cleaned, resolved for redundancy and enforced with the corresponding business rules. This is the place where most of the data used in current operation are located before they transferred to the data warehouse for temporary or long term storage or archiving.

The operational data store is a very busy area. Every single minute, data comes in from various sources which are progressively handling other transactions and goes to another database and information systems that need the transformed data. Since this place requires labor intensive applications, a mechanism should be done so as not to overload the operational data stored and not cause it to break down from handling and concurrently processing large quantities of data.

Every one in a while in a regular interval, those data which are not momentarily used for the operation should be moved to another place. For the sake of clarity, let us say that the reason why the area is called operational data store because it is the repository of the currently operational data which are used for current operations.

So, when the operational data store sees that data is not needed at the moment and the data store has already transformed the data by adding corresponding format in line with data architecture, the data will then to be moved to the data warehouse or more specifically, an integrated historical data portion of the data warehouse.

Integrated historical data are just like any other enterprise data which has generally passed through the process of extract, transform load (ETL). Since they are basically the same data, they are also contained in a database inside the data warehouse. The only distinct thing about then that differentiates them from operational data is that they more at rest.

The term historical data is very apt because these data are really relatively past in the they have already served their intended purpose. The are placed one area or may be in different areas but connected by some application tools so that they can be easily retrieve when a need arises.

Historical data are very important especially in the area of statistical analysis. For instance, if the company want to know the sale trend within the last few months, operational data alone cannot address this need and the business intelligence system will have to get data from the integrated historical database.