Using Analytics to Prioritize Data BackupUsing Analytics to Prioritize Data Backup
Data is growing exponentially, and the statistics are stunning. About 90 percent of all data was created in the past two years. By 2020, we will generate 1.7 terabytes for every human being on the planet, according to research firm IDC. For businesses, this creates the serious challenge of not only trying to figure out where to put all their data, but also keep copies of it for safekeeping.
October 12, 2016
Data is growing exponentially, and the statistics are stunning. About 90 percent of all data was created in the past two years. By 2020, we will generate 1.7 terabytes for every human being on the planet, according to research firm IDC.
For businesses, this creates the serious challenge of not only trying to figure out where to put all their data, but also keep copies of it for safekeeping. Continuing to add backup capacity to accommodate growing volumes eventually becomes impractical, not to mention extraordinarily expensive.
So businesses that take data backup seriously – 53 percent don’t do it daily, as they should – need a strategy to handle data backups that goes beyond adding more space. Instead, businesses need to focus on what data to copy. What is often lost in conversations about backups is that not all data is worth saving, because it will never be used again. Not because it sits forgotten somewhere, but because it won’t be needed again. Ever. So why spend money on backing it up?
Businesses need a smart backup strategy. And they need help from MSPs to come up with the strategy.
Saving the Business
Even though that should be obvious, some business owners and managers don’t have a good handle on what that their critical data is. This comes as no surprise to a lot of MSPs. That’s why you, as an MSP, have to be involved in this process. Your contribution could well save a client’s business if it suffers a major data loss.
Business-critical data – that which is integral to running businesses processes – has to be the first priority of any backup. Without it, the business cannot operate.
Just as important is data that falls under the jurisdiction of privacy and archival laws. This data also has to be available for recovery following an outage, though not necessarily as readily as the business-critical data needed to resume operations. But archiving and backup of this information cannot be ignored – or businesses risk hefty fines.
Intelligent Backup Systems
Having a firm grip on all this data as it flows in and out of the network from mobile devices, social media, websites and other sources, isn’t always straightforward. Some data can get misplaced or lost. In some cases, data that really isn’t needed gets saved, stored and backed up needlessly. There’s a business cost associated with that.
This can be avoided by, well, looking at data. Intelligent tiered data architecture helps figure out which information to back up and prioritize through sophisticated analytics engines. You’re basically applying the concept of data analytics to backup management to increase efficiency.
Leveraging data analyzers takes the guesswork out of figuring out which data to back up and prioritize. The analyzer can set up backups by order of importance so that, should an outage occur, a business can resume operations as fast as possible by recovering the most critical data first. Data that doesn’t need to be saved is sifted out, so it doesn’t take up valuable space or add to a company’s expenses.
Intelligent systems give MSPs another tool in showing customers the importance of backing up business data. If you can show them how to do it cost-effectively and strategically, customers are more likely to give data backup the attention it deserves.
Marvin Blough is StorageCraft’s Vice President of Worldwide Sales, where his focus is on expanding the company’s global reach by establishing channel partnerships that enhance profitability for the channel partner.
Guest blogs such as this one are published monthly and are part of MSPmentor’s annual platinum sponsorship.
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