An operational data store catalogs dynamic data generated at random intervals from sources outside typical business methods. The data is confusing and poorly referenced, requiring heavy processing before long-term archiving. Most work involves cleaning it, moving it to correct fields, correcting spelling errors, filling in missing entries, and cross-referencing data with internal databases. An operational data store has a specialized interface allowing easy movement, copying, or modification of data.
An operational data store is a way of cataloging dynamic data for further processing. This data is often generated at random time intervals and from sources outside of typical business methods. For example, sales data, generated by an automated sales web page every time a customer orders something, is operational rather than long-term. The information in an operational data store is often confusing and poorly referenced. As a result, the data is usually heavily processed before moving to a long-term archiving method.
There are two main ways to generate data for a system: by a person or by a computer. When data is generated directly from people, the information is entered into a database and is almost immediately ready for storage. When a computer generates the data, even a computer directed by a person, the data is generally less organized.
The main difference between an operational data store and a standard data store is the point of view of the people using it. When data is retained for long periods, regardless of state or data source, it is in a non-operating system. These databases make up the majority of data storage systems. It is only when the data is actually processed that its system is considered operational.
Typically, the data in an operational data store is a jumbled pile of related information. Most operational data is generated by people who don’t work directly with data systems. When a typical trader uses the database, they make sure to fill in all the necessary fields correctly. Other users, such as those accessing the database through a web portal, usually just look at an interface. Small errors in their entries or problems in the interface can cause data to propagate incorrectly in the database.
As a result, most of the work done on operational data involves cleaning it. Common tasks include moving information to the correct fields, correcting spelling errors, filling in missing entries, and cross-referencing data with internal databases. Once the cleanup is complete, most of the operational data is moved to long-term storage.
In most cases, an operational data store has a specialized interface. Because most information in a standard database requires minimal updating once finalized, it often uses a streamlined interface for presentation rather than editing. An operational data store usually works the other way around. The interface allows operators to easily move, copy or modify data in ways that standard interfaces would not allow.
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