Data loss, whether caused by equipment failure, human error, natural disasters, disgruntled employees, or cyberattacks, is a major threat to your business. If you’re not prepared, losing sensitive data can bring your business to a grinding halt. Fortunately, the following backup solutions can help prevent such a scenario.

Modern businesses use data in almost every aspect of their operations. Without immediate and constant access to it, organizations will come to a grinding halt. That's why it's critical to have data backups — in the event of a disaster, companies risk losing valuable data if they don’t have backup strategies in place.

Any business owner worth their salt knows the value of data to business. This is why it’s bizarre that many business owners don’t have a proper data backup strategy in place. Organizations of all sizes need to take a proactive approach to backing up their data, and there are several solutions they can implement to do that.

“Prevention is better than cure,” says the scholar Desiderious Erasmus and it speaks true not only in the medical field but also in technology. To avoid having a problematic storage virtualization system, here are three common mistakes to watch out for.

You’ve probably heard of cloud computing, but what about virtualization? Both are invaluable for small businesses, but it’s easy to mix them up. Learning the differences between these technologies can save you a lot of money, so let’s do a quick recap of how they work.

Implementing a virtualized data storage solution at your business is no small feat. It’s a complicated process that requires immense amounts of technical expertise. Unfortunately, getting it up and running is only half the battle. For the most efficient solution possible, watch out for the three most common management issues outlined in this post.

Recently, Amazon Web Services (AWS) announced the creation of a new data analytics tool to lighten the burden on businesses when analyzing data in the cloud. This tool, referred to as “Glue,” is meant to clean up and organize data that comes into the cloud from various sources so that it can be analyzed by business intelligence software and data analytics experts.