Not all data is created equal. Structured data, such as customer, inventory, and ordering information, resides in the neatly formatted fields of corporate databases. It’s instrumental to running the business, and companies tend to be well-versed in how to access it to support their operations.
Then there are non-database files like PDFs, Microsoft Office documents, email messages, social media posts, photos, and audio and video recordings. This unstructured data represents 80% to 90% of all new business data, according to Gartner, and is growing three times faster than structured data.
The explosion of unstructured data has put two trends on a collision course: the enterprise realization that these files are worth keeping for the valuable insights they contain and the fact that many unstructured file types are costly storage hogs.
With Opportunity Comes Challenges
Historically, it’s been common to store unstructured data informally, often in pockets of the organization where only select employees might access it. Visibility limitations have hindered efforts to fully capitalize on it.
As unstructured data grows, however, so does its value as well as its risk. For example, unstructured files often contain personally identifiable information (PII) subject to privacy laws. Moreover, valuable intellectual property, account numbers, credit card information, and other confidential data might be floating around in PDFs vulnerable to hackers looking to steal, expose, or corrupt it.
For these reasons, enterprises need scalable, affordable, and high-performance storage and management tools for unstructured data. Current, instantaneous access to data unleashes its value and allows enterprises to protect it from compromises that can create downtime, lost business, and damaged reputation. Object storage delivers these capabilities.
Enter Object Storage
Object storage uses extended, custom metadata to bring structure to unstructured content, delivering visibility into insights, trends, and sentiment related to sales, marketing, operations, supply chains, and other key aspects of the organization. Commonly used in cloud repositories, it describes and sorts data using attributes like name, creation date, and location, enabling users to find data by searching on keywords. This approach allows businesses to easily find, classify, and programmatically manage unstructured data.
Object storage got its start in data archiving. Infrequently accessed, archived data generally doesn’t require superior performance; however, unstructured data is moving quickly into primary storage use cases. For example, the cloud-native applications driving enterprises forward are built largely on object storage. Many use in-memory processing, analytics, AI, and machine learning that demand much higher data retrieval performance than backup and archiving applications do.
While object storage is the de facto format in hyperscale public cloud storage services, it’s also supported by cloud-native on-premises storage applications, such as the Hitachi Content Manager (HCM). Such systems enable hybrid storage foundations that accommodate the growing number of private/public cloud IT infrastructures under construction for workload optimization.
Takeaway
Unstructured data is multiplying, and enterprises need a way to harness it for data-driven decision-making. IT teams can augment existing storage systems with modern, agile object storage that affordably scales to enable high-performance data analytics, management, and protection.
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