Chained Data Replication is a process of replication where non-official data is replicated into another non-official data. If data are replicated from nonofficial data, they are considered duplicated data, not replicated data.
In statistics, the term official data refers to data collected in different kinds of surveys commissioned by an organization. It also refers to administrative sources and registers. These data are primarily used for purposes like making policy decisions, facilitating industry standards to be followed, outlining business rules and best practices among many other things.
Non-official data on the other hand are data coming from external sources. In business, these non-official data may come from other data sources that are randomly selected by an organization. A lot of new markets today like e-commerce and mobile technologies are commonly using more detailed data by non-official sources.
It is common for many business organizations also to publish business data outputs on their official websites and offer data as freely accessible to anybody. For another company to get these data, they are already getting non-official data integrated into their data warehouse. Problems on reliability can arise in these cases as the data managing expertise from one organization to another can vary.
As a company’s warehouse grow in bulk with a variety of data sources contributing both official and non-official, it is extremely important to employ a mechanism in order to get the relevant data needed by the company. Also because a great bulk means more labor for the hardware system within the data warehouse, there should be a mechanism to manage all the data so that the data warehouse will not break down and suffer the business operation of the company.
Chain Data Replication involves having the non-official data set distributed among many disks which can provide for load balancing among the servers within the data warehouse. Blocks of data are spread in many clusters and each cluster can contain a complete set of replicated data. Each data block in each cluster is a unique permutation of the data in other clusters.
When a disk fails in one of the servers, any access for data from the failed server is automatically redirected to the other servers having disks containing the exact replica of non-official data.
In some chain replication implementations, computers allow replicas and disks to be added online without having to move around the data in the existing copy or affecting the arm movement of the disk. For instance, in any unforeseen even where there arises a need to increase number of replicas because of the high increase in demand, additional replica can be loaded fro tape and stored automatically into the newly installed disks.
During the disk installation and loading of replica, services which are providing by the existing array of disks are not affected as there are no additional I/O requests to array of disks and replicas are generated by the loading process itself. When the loading of replica is done, new replica can already start servicing data requests from various sources.
In terms of load balancing, Chain Data Replication works by having multiple servers within the data warehouse share data request processing since data already have replicas in each server disk.
Everyday, data warehouses are constantly extracting, cleansing, transforming business data and loading them into the warehouse. Today’s businesses are not just powered by company intranets but the internet as well. If is extremely important to have a powerful data warehouse infrastructure because with the internet, the company is exposed to billions of user every single minute. Chain Data Replication will surely be a beneficial methods to make use of all these data.