Data is an invaluable resource for any organization operating in the digital world. An organization’s ability to collect, analyze, process and act on raw data sets it apart from its competitors while also offering an edge in driving customer experience, marketing intelligence, R&D, and innovation opportunities, etc. Although many organizations are now adept at handling structured data, managing unstructured data remains a challenge:

• Only <1% of unstructured data (almost 80% of the total raw data) is utilized as there is no efficient mechanism to process it – Harvard Business Review
• Only 18% of organizations reported being able to take advantage of unstructured data – Deloitte 2019 Data Survey

Extracting relevant and meaningful insights from unstructured data while catering to modern, data-heavy business needs is one of the biggest challenges faced by enterprises today. The table below shows some of the typical challenges associated with managing unstructured data when using traditional storage along with various new-age technologies:

Table 1: Typical Challenges Associated with Unstructured Data Management

Object storage has been able to eliminate these limitations of traditional storage to a great extent. Enterprises can adopt object storage to extract the maximum value out of the unstructured data. It works on a distributed file system, handling massive data that can help service providers extend extremely cost-effective and highly scalable solutions on the public cloud. It is scalable up to hundreds of petabytes, under a single namespace without degrading any performance. In object storage, the erasure coding technique maximizes the usable capacity, offers data management functionality, and minimizes the overall cost, unlike in traditional storage technologies like versioning, customization metadata, and embedded analytics.

IDC has projected the object storage market to reach USD 14 Bn and a combined study by 451 Research and Western Digital has predicted that 80% of enterprise data will be on object storage by 2021.

Key features of object storage are:

• Scalability: Can seamlessly extend the capacity by adding new nodes
• Speed: Faster retrieval and no directory system with its associated bottlenecks
• Lower Cost: Less expensive in comparison to traditional storage as nodes can auto-scale with zero downtime
• Ease of Access: Users can access, analyze, and store the data anywhere via metadata
• Multi-site Access: Provides geo-protection against any kind of site failure
• Kubernetes Integration: Integration helps in orchestrating containers across multiple hosts and auto-scaling containerized applications

An object storage system on top of Kubernetes can help in easy management of distributed containerized applications, even across multiple data centers. It can act as a single pane of glass to control the data management and the orchestration of distributed object storage pools, irrespective of them being distributed or local across the regions or data centers.

The need for digital transformation and unstructured data challenges, are the key drivers for enterprises to adopt object storage. Object storage can play a crucial role for organizations to become more agile, auto-scalable, highly flexible, access any device instantly, enable multiple apps on one system, and create a scalable environment on cloud. Few of the popular use cases of object storage are:

• Video/Image Distribution: Faster growing IoT data (video files and images) can be maintained and accessed anytime, anywhere via object storage
• AI/Edge Big Data Storage: Can store unlimited data in a simple and cost-effective way
• Backup and Recovery: Protects the data by replacing tape and backing up through object storage, thus simplifying archival processes and streamlining backup operations. It has an immutable backup copy feature useful for threats such as ransomware
• Data Archive: Reduce cost and complexity with easy archival and access whenever required
• Tape Replacement: No upfront cost unlike tape library, decreasing the overall cost and maintenance
• Active Archive Always-On: Keeps data available and quickly accessible from anywhere with the help of RESTful APIs
• Object Storage Mission Control: One-Stop Solution for On-Premises and Cloud Management

Object storage is one of the most efficient ways for enterprises to cope with burgeoning unstructured data. Massive scalability and metadata features empower object storage to manage vast video and audio data; and create data lakes for quick data retrieval. Enterprises can aggregate massive data, layer modern applications on top of the data storage, and apply AI and ML for business-critical data analytics leveraging object-storage solutions. It provides scale-up solutions like host-based software, appliances, and gateways that help customers run their applications in private, public, or at the edge network, driving innovation and protecting against ransomware attacks. Object storage metadata helps analysts and data scientists identify and manage storage data easily, enabling enterprises to create better strategies and drive growth.

Most of the leading public cloud storage providers like AWS, Azure, IBM, and Google have adopted object storage because of its seamless unstructured data management, scalability, and flexibility over file-based methods. Integration of the object storages with current IT infrastructure is quick and easy, helping customers to auto-scale whenever required, leading to an enhanced customer experience overall.

HCLTech Infonomics has various object-based solutions that have been implemented in several complex and critical customer environments. HCLTech has a vast partner ecosystem with a large pool of trained/certified resources.

Learn more about HCLTech and the details about our partnerships with the leading object-storage solution vendors here: /about-us/alliances.