“Digital transformation” must be one of the most used — and the most misused — words in corporate IT at the moment. Though everything from automating email outreach to configuring AI-powered cybersecurity platforms has been called “digital transformation”, at the most fundamental level digital transformation can be defined quite simply: it is the practice of integrating technology into your business.
When looked at in this broad way, it’s possible to see that any process of digital transformation relies on a few key components. One is the expertise available to you to design digital systems, and a second is the computational resources available to you. A third, and for most organizations the most important, is the type and amount of digital storage available to you.
This is because almost all of the systems and processes involved in digital transformation rely, to a greater or lesser extent, on data storage. Some “merely” require you to increase the storage available to you. Others all but necessitate the development of novel storage architectures such as a data fabric. In this article, we’ll look at each of these technologies in turn, and explain their implications for data storage systems.
If you have not already deployed edge systems in your business, it’s a fair bet that you will be required to in the near future. Many new types of interface, and above all voice-activated systems, process such huge amounts of data on an ongoing basis that they require data to be stored and processed close to where they are being generated and used. The process of moving computational and storage resources closer to front-line devices is known as edge computing.
At its core, edge computing is all about managing data storage. Merely creating storage space sufficiently close to the edge can be a challenge, and managing this data to avoid undue duplication can also be difficult. For this reason, it’s very important that organizations have rigorous storage infrastructure in place before they make the move to edge computing.
The “hybrid cloud” is another one of those phrases that is currently beloved of IT consultants, and another that actually denotes a simple idea when you come down to it. Hybrid clouds are storage architectures that make use of both public cloud systems and on-premises clouds.
Though hybrid clouds are often thought of as a way of integrating systems, the truth is that without careful management they can have the opposite effect. At the most fundamental level, hybrid clouds divide data storage repositories from each other, and fragment your data by definition. That’s why, alongside hybrid clouds, we’ve seen the rise of software-defined storage — a way of hiding the complexity of hybrid cloud models for those users who don’t need access to the inner workings of your data architecture.
Read more: Making Storage Work Across Hybrid Clouds
Unstructured data has always created challenges for software engineers, but this is about to get a lot worse. The amount of unstructured data that organizations need to store is about to explode. In part, this is due to the increased reliance on social media platforms and media-heavy marketing and website content. This means that even website backups now consist of huge amounts of pictures, audio, and video content that can’t be neatly slotted into an efficient database.
There are several responses to this challenge. One of the newest, and arguable one of the most powerful, is object storage. This is a storage paradigm that seeks to retain the relationships between elements of your data structure, while at the same time offering you the flexibility to move data around as required. Moving to an object storage approach is therefore invaluable for companies looking to push their digital transformation activities to the limit.
As digital transformation processes continue across many sectors, even the idea of the “backup” is changing. Five years ago, most companies saw their backups as an insurance policy against accidental loss or (if they were aware of such things) ransomware attacks. This typically meant copying the contents of hard disks to other hard disks, which then languished deep in the server room of corporate offices.
Now, we are starting to recognize that backups have a value beyond mitigating data loss. It’s now possible to run analytics on your backed up data, for instance, while your primary data store is being used by your customers and staff. This makes analytics much more efficient, but only if the physical infrastructure that underpins your backups is fast and adaptive enough to be used in this way.
Move to a more modern form of backup, in other words, and you’ll not only find that your backups are more secure — they might actually become useful as well.
Most digital transformation processes, by their nature, require access to data at a faster rate than the manual processes they are replacing. For this reason, one of the most important things that organizations can do to prepare for digital transformation is to upgrade their data storage infrastructure before they start to plan digital transformation.
Thankfully, there are no lack of options in this area. If you haven’t looked at the data storage options available to you for a few years, you might be surprised as to how much things have moved on. Many organizations, for instance, are now looking at expanding their use of NVMe (non-volatile memory express) flash storage, sometimes as a complete replacement for “traditional” hard drives.
The Bottom Line
Ultimately, any process of digital transformation will rely on the data storage you have in place. This means that successfully transitioning to digital processes will always involve upgrading your storage infrastructure, learning how to use software defined storage, and maybe even a radical rethink of the way you store data.
Read next: 6 Developments in Healthcare Data Storage