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As Cybersecurity Awareness Month draws to a close, it’s a good time to reflect on the evolving landscape of digital threats. One critical area often overlooked is unstructured data security. While organizations are making proactive efforts and investments to protect structured data assets and systems, the vast majority of data generated today – a staggering 80% to 90%, according to experts – is unstructured. This type of data is growing at a rate three times faster than its structured counterpart.
Unstructured data includes everything from emails and documents to images and device telemetry. Ignoring its security is like locking the front door but leaving all the windows wide open. The growth in unstructured data is driven in part by activities that have become ingrained in daily work and personal life, including the increased use of digital communication and collaboration tools.
The rise of remote work and the increasing use of platforms like Microsoft Teams, Slack, and Zoom are generating massive amounts of unstructured data in the form of chat messages, video recordings, and shared files. The proliferation of social media platforms and the growing volume of associated online content, including images, videos, and text, are also fueling the growth trend.
This surge is further amplified by the relentless proliferation of mobile devices. Equipped with high-quality cameras, smartphones and other edge devices capture and transmit unstructured data such as photos and videos.
Collaboration tools and social media platforms act as catalysts by facilitating the creation and sharing of unstructured content. They provide users with intuitive interfaces and powerful features that encourage them to generate and exchange various forms of unstructured data. For instance, collaboration tools allow teams to seamlessly share files, engage in video conferences, and exchange instant messages, all of which contribute to the growing volume of unstructured data.
Similarly, social media platforms empower users to express themselves through images, videos, and text, further fueling the growth of unstructured data. The ease of use and accessibility of these platforms, coupled with the increasing reliance on digital communication, are driving the exponential growth of unstructured data, presenting both challenges and opportunities for organizations worldwide.
As more industries and individuals adopt Internet of Things (IoT) solutions, including connected devices and sensors, the number of data-generating devices increases dramatically. While exact figures and estimates differ slightly, there is consensus that the number of IoT devices is in the range of 15 to 20 billion. This does not represent a linear increase, but a compounding effect where each new device adds to the existing data generation capacity, leading to an explosion in the overall volume of unstructured data.
Data as Fuel for AI and ML Engines
Furthermore, advancements in sensor technology and communication protocols allow for more frequent and granular data capture of sensor readings, telemetry, event data, and log files, which further amplify the growth rate. This constant influx of unstructured data presents significant challenges for cloud storage, processing, and analysis, pushing the boundaries of current data management technologies.
Artificial intelligence (AI) and machine learning (ML) applications require vast amounts of unstructured data for training and development of large language models (LLMs), further fueling the growth of unstructured data. LLMs, like those powering sophisticated chatbots and AI assistants, learn and evolve by analyzing and identifying patterns within massive datasets of text, images, audio, and video. The more data these models are trained on, the more comprehensive and nuanced their understanding of the world becomes, leading to more accurate and insightful outputs.
This reliance on unstructured data creates a cyclical effect. As AI and ML applications become more prevalent, the demand for unstructured data to train them increases. In turn, this demand drives the development of new tools and technologies designed to capture, store, and process unstructured data more efficiently.
For example, advancements in natural language processing (NLP) allow machines to better understand and extract meaning from text, while computer vision enables them to interpret images and videos. These technologies are essential for converting raw, unstructured data into a format that can be used to train and refine AI and ML models.
The growth of unstructured data is expected to continue in the coming years, driven by the ongoing digital transformation of businesses and the increasing adoption of AI and ML technologies. Organizations that can effectively manage, analyze, and secure their unstructured data will be well-positioned to gain a competitive advantage in the data-driven economy.
But it’s not just the sheer volume that’s challenging. It's the fact that much of this data is unstructured, making it difficult to organize, analyze, and secure. Enter unstructured data management platforms, a new breed of technology designed to tame this digital deluge. These hybrid cloud file and data services platforms offer a centralized solution to manage and protect your data, no matter where it resides – on-premises, in the cloud, or at the edge.
The Panzura hybrid cloud file platform, CloudFS, for instance, is underpinned by a high-performance global file system that consolidates unstructured data into a single, easily accessible repository, enhancing collaboration and data security across distributed environments.
But managing this data is only half the battle. Securing this valuable, yet vulnerable, data means organizations need to prioritize data governance. This means understanding what data they have, where it resides, and who has access to it. With increased scrutiny on data privacy and security, a cohesive data governance strategy is no longer optional – it’s essential for mitigating risks and unlocking the long-term potential of data for competitive advantage.
Panzura Symphony takes this a step further by offering comprehensive data operations under a single pane of glass, enabling automated, exabyte-scale data discovery, risk and compliance analysis, and dynamic data movement orchestration.
Rise of Unstructured Data Management Platforms
The rise of these unstructured data management platforms is revolutionizing how organizations handle the ever-growing volume of data generated from diverse sources. These platforms offer unified data management, providing comprehensive solutions for managing and securing unstructured data across various repositories, including on-premises, cloud, and edge environments.
They incorporate data-centric security features, such as access controls, encryption, and data masking, to protect sensitive information. By automating and orchestrating tasks like classification, policy enforcement, and threat response, these platforms reduce manual effort and boost efficiency. This automation allows organizations to focus on extracting valuable insights from their data while ensuring its security and integrity.
Panzura Symphony, a data services platform, addresses many challenges enterprises face with unstructured data. It provides comprehensive data operations under a single pane of glass, enabling customers to perform automated, exabyte-scale data discovery and assessment, risk and compliance analysis, and dynamic data movement orchestration. Symphony integrates natively with major file systems and protocols, supporting on-premises, private, public, and hybrid cloud object storage.
Focus on Data Risk and Compliance
In today’s data-driven world, organizations are increasingly focusing on data risk and compliance, particularly for unstructured data. This emphasis stems from a growing recognition of the risks and opportunities associated with this type of data. Data discovery and mapping are crucial first steps, allowing organizations to gain a comprehensive understanding of their unstructured data landscape. This involves identifying the location of sensitive data, determining who has access to it, and understanding how it is being used.
This knowledge is essential for managing risks and ensuring compliance with regulations such as the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and Health Insurance Portability and Accountability Act (HIPAA), which mandate robust security measures for unstructured data containing Personally Identifiable Information (PII).
PII includes any data that could potentially identify a specific individual. This can include direct identifiers like names, social security numbers, and email addresses, as well as indirect identifiers like location data, IP addresses, and medical records. These regulations focus on protecting PII and giving individuals more control over their personal data including how it is collected, used, and shared.
Panzura Symphony allows teams to achieve compliance, maintain it, and expand across all areas of their unstructured data landscape through thorough analysis and policy enforcement, seamless data movement, and evidence-based reporting for stakeholders.
With unmatched insights into data demographics and comprehensive, shareable, and exportable reports, Symphony helps organizations better identify blind spots within their growing data environments. This enables them to better handle regulatory obligations and reduce risks, ensuring a more secure and compliant data estate.
Implementing clear data compliance and retention policies is critical. These policies help minimize risks by ensuring that data is securely retained and then disposed of when it is no longer needed, reducing the potential for data breaches and ensuring compliance with legal and regulatory requirements. By focusing on data governance, organizations can effectively manage their unstructured data, mitigating risks and unlocking its full potential.
AI-Powered Data Security
In today’s increasingly complex digital landscape, traditional data security measures often struggle to keep pace with the evolving threat landscape. AI-powered data security solutions offer a much-needed edge by leveraging the power of machine learning and advanced analytics to provide comprehensive protection at a speed that can minimize the blast radius.
Intelligent threat detection systems utilize AI algorithms to sift through massive volumes of unstructured data, identifying patterns and anomalies that may indicate ransomware attacks, malware infections, or even insider threats that would likely evade conventional security tools. Coupled with a solution that can interdict attacks at the source, shutting off the affected user accounts to stop attacks and minimize the damage, organizations can substantially strengthen their security posture.
Furthermore, AI excels at automating the tedious and repetitive tasks associated with data classification, accurately categorizing sensitive information like PII, protected health information (PHI), and valuable intellectual property. This workflow automation allows for the seamless application of appropriate security policies and controls, ensuring that sensitive data remains protected.
AI’s predictive capabilities also play a crucial role in proactive security. By analyzing past incidents and emerging trends, AI systems can forecast potential security risks, empowering organizations to take preventative measures and mitigate breaches before they occur.
Data Loss Prevention (DLP) tools are evolving, incorporating AI to better understand and safeguard sensitive data within unstructured data. These advanced DLP systems can identify, monitor, and control the movement of sensitive information, effectively preventing unauthorized access or the disastrous exfiltration of critical data.
The explosive growth of unstructured data, fueled by social media, hybrid work models, IoT devices, and AI/ML applications, presents significant challenges for organizations, not the least of which is access and security at the edge.
Traditional data management methods struggle to cope with the sheer volume and complexity of this data, making it difficult to extract valuable insights and ensure its security. This necessitates a shift towards unstructured data management platforms and a strong emphasis on data governance.
For example, organizations that rely on Panzura CloudFS can extend secure data access and control to the edge with additional, seamless platform capabilities. They can easily manage and protect their data wherever it resides, including remote offices, data centers, and IoT devices.
By adopting comprehensive data management platforms and prioritizing data governance strategies, organizations can effectively manage and protect their unstructured data. These platforms offer advanced security measures, automation capabilities, and valuable insights, empowering organizations to harness the full potential of their data while mitigating risks in an increasingly data-driven world. The future belongs to those who can effectively tame the digital deluge, unlock the power of unstructured data, and accelerate data delivery.
