Change data capture is the process of recording and saving version records in data systems. It assigns indicators to data items that change when data changes, notifying the system and saving previous versions. Data versioning is important for archiving and error checking. Methods for creating versions include special markers. Large-scale systems are found in data warehouses and open access databases.
Change data capture is the process of locating, recording, and saving version records in data systems. In most cases, change data capture systems work by assigning certain indicators to the data that refer to specific data items. When data changes, these indicators also change. This notifies the capture system of the change data and saves the previous version of the data, giving users and systems access to old and new data. These processes are common in large data storage systems such as data warehouses and web-based data systems.
Data versioning is considered to be a very important aspect of data archiving. When one piece of data is overwritten by another, the original piece of data cannot simply disappear. This would wreak havoc if that information was important to an ongoing process or business record.
Versioning different data is at the heart of change data capture. If a single piece of information changes five times, the system must remember each of the five values and when they changed. This is important for both long-term record keeping and error checking. For example, if a worker were to input a sales figure into the wrong part of a database, they could disrupt a huge amount of information. Versioning allows the company to roll back that number if needed.
There is no pre-defined method for changing data capture. Different data systems use their own versions, often developed in-house to fit your specific style of data storage. Even so, there are a handful of commonly used methods. It is not unusual for a single system to have several change data capture methods operating on the same system. Often, each method specializes in a certain type of capture or operates as a redundant security system.
The most common methods of creating different versions of data are special markers in the data. These indicators are located in a special row or column in the data that tracks when changes occur. Change data capture scripts monitor these areas for changes and track the changes made. These special cells might contain version numbers, timestamps, or proprietary data strings.
The two most common places to find large-scale change data capture systems are in data warehouses and open access databases. One of the main strengths of data warehousing is the constant and complete backup of data. As long as a user subscribes to their services, these systems never get rid of anything. Open access databases, such as Wikipedia, use versioning to prevent tampering and keep track of which users made which changes. While Wikipedia’s versioning may not be as comprehensive as those used in data warehouses, it is often reviewed by multiple users.
Protect your devices with Threat Protection by NordVPN
