"Object storage is big data's answer to storing and managing ever-growing unstructured data in units called objects. These objects, or simply unstructured data, can be standard data, metadata, or a unique identifier. But it's not organised how you might think. Rather than being stored in folders or a hierarchical path, they're accessed through multiple paths. It's a flat data environment approach that also applies to structured data such as photos, videos, emails, etc."
"The challenges of big data tell us why object storage is becoming so essential. The sheer volume, velocity, and variety of big data are creating a massive strain on existing, traditional data storage servers and processing infrastructures. And with such massive data sets come security and privacy risks. An even bigger risk is that there's a lack of skilled professionals with the required training to manage and analyse big data. It's having a massive impact on data quality and storage."
Big data adoption and market value are rapidly increasing, with substantial growth between 2024 and projected 2033. Data creation is exponential as nearly every online action contributes to extremely large, complex datasets that traditional processing tools cannot manage. Volume, velocity, and variety place heavy strain on existing storage and processing infrastructures and introduce security and privacy risks. A shortage of skilled professionals exacerbates data quality and storage challenges. Object storage stores data as objects with data, metadata, and identifiers in a flat namespace, enabling public cloud providers to distribute and reliably archive vast unstructured datasets across geographic zones.
Read at Business Matters
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