big dataBig data occupies a massive data storage capacity. A backup process for your big data will consume a lot of storage and network resources and is not an easy task. This raises the question is it worthwhile to back-up your big data. In this article, I’ll discuss this question and give several tips for big data backup.   

The Importance of Backup for Big Data

Big data applications were traditionally designed to analyze past product sales and forecast trends and were not considered business-critical. Big data analysis has evolved to be an essential tool for business daily operation. Many customer service applications are using big data analysis to interact with their customers. 

Big data management is dependent on the reports generated by big-data-based business analytics tools for daily decisions. These reports can help in making decisions to improve services, product turnaround, and profits. Companies invest a lot in big data storage and software. In order to protect this investment, you should regularly back up your big data storage. 

Backup in the Cloud vs On-Premises

You can use on-premise storage or a cloud storage service, or both, for big data backup.

On-premises big data backup

Big data backup requires high volumes of data to be processed at a high rate of input/output operations per second (IOPS). On-premises storage devices can be selected to meet these requirements. If a high IOPS rate is required, an on-premise storage device is recommended.  

Big data backup in the cloud

Cloud-based services are very versatile and can be a solution for most of your big data backup needs. Many companies are using cloud services for big data storage and processing. It would be efficient to also backup big data over the cloud. There are several advantages to using a cloud service. Cloud backup can be replicated over multiple locations for redundancy. The data you back up to the cloud is secured with advanced encryption techniques. 4d-dc.com provides colocation data centre services, cloud solutions with cost-saving and reputation-protecting resiliency.  

On-premises and cloud hybrid solution

You can use both on-premises infrastructure and cloud services for your big data backup. In this way, you can efficiently use all these resources to make your backup process cost-effective. Having your data backed up on-premises and over the cloud can add another layer of protection.

Using both solutions can also be helpful for disaster recovery. In the case of on-site disaster, cloud data backups ensure that data remains available. But it may also make sense to keep your backups on-site. In cases where the disaster did not damage the backup volumes, the data will be restored more quickly compared to the remote sites.

Best Practices for Big Data Backup

Here are several tips on how to back up your big data: 

  • Backup in a remote location—when protecting your big data from physical disasters, such as fires, earthquakes, and storms, it is important that your backup resides in off-site and remote locations.
  • Data backup is not enough for disaster recovery—you should remember there is a difference between data backup and disaster recovery. Normally, you restore from your backup a particular file or directory which was corrupted or overwritten. But in a case of disaster recovery, you are going to recover all your data. This may take a long time. When a disaster occurs, you need a disaster recovery plan to ensure your big data operations return to normal as soon as possible.
  • Using snapshots—snapshots are used as a backup copy to protect against data loss. Snapshots can be used for big data backup only when the data is not changing rapidly. If you are storing your big data on Amazon cloud, you can use the AWS snapshots service.
  • Data compression—you can decrease your big data size by compressing it. This will result in reducing storage costs and bandwidth usage. For data compression, you can use data deduplication. Data deduplication is a process that eliminates redundant data blocks within a dataset.
  • Schedule frequent backups—to prevent loss of data, you should know how often your data is changed. According to this, you should set the frequency of your backups. You can also create a different backup schedule for different data blocks. For example, you can set your backup application that specific data blocks are backed up once a day, while others are backed up only once a week. This will eliminate unnecessary backups, reducing storage and costs.
  • Backup retention—you should consider the time period you want to keep your backup on the storage server. Keeping a long history of your big data backups will consume a lot of storage space, which eventually will run out. Instead, you can set a more feasible retention policy. An example of such a policy is: hourly and daily backups are kept for a week, weekly backups are kept for a month, and monthly backups for six months.
  • Backup security—a good security practice is to have your big data backups protected by strong data encryption technology. This will ensure that in case of unauthorized access to your backup, the data will be unusable. The data should be encrypted while it is at rest, inside the storage device, and while it is on the move from one location to another. 

Wrap Up

Big data has an important role in the success of many companies. These companies are facing the challenge to back up their big data. Not having an efficient solution for this may result in potential data loss which may cost a lot of money. In this article, we’ve seen the importance of protecting your big data with regular backups, as well as several tips big data backup.