Transforming Raw Data into a Controllable Corporate Resource
In today's data-driven world, organizations are grappling with the challenge of extracting meaningful information from their vast pools of unstructured data. This unstructured data, which can account for up to 90% of an organization's total data, includes emails, images, videos, audio, sensor data, and more.
Traditional data management processes often require manual identification, classification, and relocation of data across systems, a time-consuming and laborious task. However, automation is stepping in to change this.
Automation enables organizations to orchestrate the movement, storage, and governance of unstructured data across their environment. By doing so, it turns fragmented, unwieldy environments into manageable systems where data can be governed throughout its lifecycle. This, in turn, helps build a sustainable and manageable environment that can actually deliver on unstructured data objectives.
One of the key benefits of automation is its support for capacity planning. By relocating inactive data to lower-cost tiers, it reduces the volume of high-performance storage required while maintaining access to critical files when needed. This not only saves costs but also ensures that critical data is always readily available.
Automation also plays a crucial role in supporting AI and machine learning initiatives. It can identify data suitable for model training or inferencing and move it to the correct storage tier, thereby streamlining these processes and improving their efficiency.
Visibility into unstructured data is essential, but action is also required for effective data management. Automation provides this action by implementing clear policies based on access patterns, content type, or age. This proactive, policy-based approach is necessary to address these issues at scale.
Shifting from reactive, manual processes to this proactive model is particularly beneficial for IT Infrastructure and Operations teams. Automation helps mitigate the need for continual hardware investment or additional headcount by automating repetitive data management tasks.
Moreover, automation supports hybrid and multi-cloud strategies. It enables data to be copied to the public cloud for burst operations, aggregated from edge locations for central analysis, or distributed to remote sites without manual intervention.
GRC teams also stand to benefit from automation. Workflows that enforce data hygiene at scale reduce exposure and contain the potential impact of breaches, non-compliance, or other governance failures.
In conclusion, the gap between data growth and an organization's ability to exploit it efficiently is widening. Automation provides a solution to this challenge, turning complex data management tasks into manageable, policy-driven processes. By embracing automation, organizations can transform their data management practices, leading to improved efficiency, cost savings, and better decision-making.
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