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Implementing Unstructured Data Management in Today’s Multi-Vendor, Multi-Cloud Ecosystem

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Read more about author Michael Jack.

One of the challenges many organizations face is managing unstructured data’s impact within today’s diverse multi-cloud and multi-vendor infrastructure environments.

For IT professionals, it can be difficult to know where to start, mainly because there are many storage technology companies with their own take on unstructured data. By separating data management into four key categories, however, it’s much easier to bring some clarity to what each vendor type has to offer across the various elements of the value chain.

1. Cloud and Storage Vendors

Whether in the cloud or on-premises, cloud and storage vendors deliver high-performance, reliable, and proven unstructured data storage solutions. Today’s industry ecosystem can handle any amount of data – and do so while offering basic data protection solutions alongside various other very relevant capabilities.

When it comes to managing unstructured data across today’s complex multi-vendor and multi-cloud environments, however, their claims are less convincing. They have in common the starting point of putting customer data on their storage – an approach that immediately defeats the reason for implementing a hybrid environment. Add to this the tendency for their software-based data management services to be somewhat under-funded and it’s easy to see why this hasn’t evolved as an area of specialization in this niche of the technology industry.

2. Backup Vendors

Backup vendors perform a pivotal role in today’s data-hungry organizations, offering a wide range of technologies used to restore data to an original platform or applied to deliver near-instantaneous recovery.

While organizations worldwide rely on backup vendors to protect their structured data, delivering backup for unstructured data is more problematic. Most vendors begin with the assumption that users must upload data to their platform to begin the data management process. But the most serious problem with data backup methods is that they always begin with a snapshot rather than the live, continually changing primary data.

3. Data-Value Applications

At the end of the value chain, data-value apps are the most effective at extracting business value from data. In this context, business apps reign supreme, whether they’re used for analytics, research, regulatory compliance, security, or any number of other purposes.

The problem is, that business applications aren’t designed to scale with today’s unstructured storage systems. For instance, they cannot sort out the appropriate data in multi-petabyte, billion-plus file environments, and as a result, they require assistance locating the appropriate data.

4. Vendor-Neutral Data Management Software

This leads us back to the only real multi-vendor, multi-cloud option: vendor-neutral unstructured data management software that is not hampered by the limitations associated with storage and cloud vendors, backup vendors, and business value applications.

Instead, these software solutions can manage enterprise-scale workloads across any storage or cloud environment – and work directly on dynamic production data instead of a recent (or not-so-recent) copy.

Releasing the Potential of Unstructured Data

Moreover, vendor-neutral data management software delivers solutions for the issues IT leaders find most challenging. For instance, by facilitating intelligent cloud adoption, transferring data to less expensive on-premises storage, enabling IT teams to decommission wasteful storage, and removing redundant, obsolete, and trivial (ROT) data, organizations can focus on cost control – a vital consideration of any rounded strategy.

Enterprises are also increasingly aware of their performance against ESG policies and issues such as CO2 reduction targets. By giving enterprises the ability to visualize which of their storage is powered by renewables or using the most energy, it becomes possible to move data to more cost-effective storage options or delete ROT data to reduce environmental footprint.

Then there’s the issue of risk reduction, whereby effective data management software enables IT, leaders, to see what data they have, where it resides, why they have it, and who owns it. Organizations operating with this level of insight can focus on their most useful unstructured data, eliminating anything that presents additional and avoidable risk.

Ultimately, organizations everywhere are building their volumes of unstructured data with the hope or intention of deriving additional insight. With the ability to move data to the right place, at the right time, and remove what isn’t required, IT teams can focus on delivering the latent value of unstructured data and turn potential benefits into reality.

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