Very few kiwi businesses have defined disaster recovery (DR) plans for big ‘big data’, which is strange due to the fact that big data has and will continue to play a more mission-critical role in companies – so it’s no surprise when we say that DR should become a focal point for you and your business.
Despite what experts say, many business owners do not agree on the importance of big data and the need for a DR plan. However, with business environments becoming more dependent upon analytics to respond to changing consumer behaviours and strategically dependent on analytics for business outcomes, it is only a matter of time before IT starts getting asked about its plans to back up, restore, and recover from a disastrous big data outage.
Big data requires a different set of rule when it comes to DR, so IT departments that develop a big data DR plan should consider these key points when formulating theirs.
1: How quickly will you need to restore big data?
Rapid recovery should be the theme for DR plans that are built for big data required for near real-time analytics. A cloud-based data storage option might be the answer, or onsite rapid storage options such as ongoing replication of in-memory storage on multiple servers. This may not be needed instantly, but It really depends on the data type and how mission critical it is to the functioning of your business units.
2: Which data should you recover?
Big data is massive — you don’t need to target all of it for rapid disaster recovery. Meetings should be held with end business units to gain a consensus on which data is to be recovered in a DR effort. Data retention plans should be in place so that extraneous data is not needlessly stockpiled, which will only extend data recovery times.
3: What is your big data recovery point?
To answer this question you need to determine in what “form” you want to recover your big data. In other words, will you be recovering “raw” big data that appears just as it is when it first enters your systems? Or will your strategy be to recover big data that has already been extracted, transformed, and loaded into a refined form of big data that analytics can actually be performed on?
4: Update your vendor contact lists, and practice your DR
Big data DR plans need to be coordinated and tested with end user departments and vendors. Getting the big data vendors to the DR table might be most difficult because, thus far, their enterprises clients haven’t expected much.
Do you have a big data DR plan in place?
If not, it might be worth getting in touch with us. Visit our website today and give us a call on (09) 526-1800 or send us an email at firstname.lastname@example.org and let us help you get started.