More and more companies are using technologies for handling “Big Data”. It means that either a business already has a plan in place or it is in the process of making one. But most of the companies collectively believe that there is much to be achieved technologically in order to be able to manage and use Big Data. Reports suggest that nearly three-fourth of the companies feel that their enterprises could become more consolidated if they could connect all the data. So, the common perception amongst modern businesses is that they need more data privacy and better real-time data analysis. Another feature which is found to be lacking in most businesses is a comprehensive business continuity plan which will take care of data recovery in disasters. So, CompTIA ends its report by saying that companies need to look for options for disaster recovery and business continuity through cloud backups.

Why is Cloud Backup Services Needed for Big Data?

Modern businesses have access to a huge amount of information and this is why it needs to be organized and evaluated properly. Once this is done successfully, the companies can carry out actions which may have been impossible earlier. So, for businesses, data management has suddenly become the topmost priority. This is because this analyzed data is now being used by companies to understand customer needs better, to calculate business goals, to ensure that data that is stored outside is well protected etc.

Since businesses are spending more and more funds on data, it is only natural that they will want the data to be backed up so that users can access it every time they need to. The best way to make sure that data remains accessible, secure, private and recoverable is to sign up with a good cloud service provider for comprehensive disaster recovery and business continuity solutions.

- It was earlier believed that data replication would not need separate recovery tools. So, most Big Data platforms made multiple data copies and then distributed these across various servers. Data redundancy of this kind was thought to be helpful for guarding against hardware failure. But, in situations when there are errors caused by users or accidental data deletion or data corruption, data loss is inevitable and these will automatically spread to all data copies.

- Another reason which has reiterated the need for cloud backup solutions for Big Data is that earlier it was believed that data which is lost could be recovered easily and created from original data. This would work however only if all the original data was available. Moreover, in most situations, this data is usually inaccessible or has been accidentally deleted. Even if the company was able to retrieve all of the original data, rebuilding it is going to be a time-consuming affair.

- When you must make backups of petabytes of Big Data, the costs are huge. Not only do these need heavy investment, they are also time-consuming. To deal with this problem, it is possible to separate data subsets which the business needs and back that up only.

- Earlier it was also believed that the remote disaster recovery copies could work like backup copies. It was thought that keeping backups of data in remote servers is wise as it can be safeguarded against earthquakes and fire outbreaks. To do this, data must be replicated regularly from the data center which produces it to the data center that recovers it. But, all changes made in the first will be transferred to the second site including corruptions and accidental deletions. This means that you cannot use the DR copy as the backup copy. Instead, this reinforces the need for cloud backup services.

- Writing the backups for Big Data may be easy when you have resources. But modern companies deal with huge volumes of data which is spread across many platforms. So, writing or testing scripts for all these environments is not going to be easy work. One would need to write scripts for every platform for backing up the data; the script also has to be regularly tested and updated to be able to support new features. All this amounts to big costs and you need expertise to be able to create good scripts.

- It was also previously held that the disaster recovery process for Big Data was small. But there are many hidden and additional costs involved in this process. You will need to pay more for people who will run such scripts and make sure that backups are done successfully. You will have to spend money for storing the backups and also pay for downtime costs, if any. The costs will only become bigger as the Big Data world keeps growing.

- Snapshots were considered to be easy and effective means for backing up Big Data. While snapshots may be used for automating backup processes you will need manual intervention to make sure the backed up data is consistent. Moreover, snapshots work best when data is not constantly changing. Finally, recovering data from snapshots is tedious because the database administrator must identify the files which correspond to data which must be restored. Errors in this can cause permanent data loss. All these factors necessitate the use of cloud backups for Big Data recovery.

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