Managing Data Deduplication with Concentric AI

In today’s business landscape, in which data is proliferating at an unprecedented rate, organizations are looking for innovative solutions to help them manage this data deluge.

If every byte of data weaves a story, businesses are repeating the same narratives — duplicating the same information, consuming space, and clouding clarity. Enter data deduplication, which sifts through the noise to ensure that each story is told just once.

What is data deduplication?

At its core, data deduplication is a sophisticated form of data compression that can eliminate redundant copies of data, ensuring that only one unique instance of the data is retained. While data deduplication’s key function is preserving storage space, it can also serve as a strategy that improves backup times, increases network bandwidth, and boosts an organization’s overall data management efficiency.

In the context of data security, however, data deduplication is equally critical in that it can reduce the risk of data residing in too many places or being shared with too many parties.

Storing duplicate or near-duplicate data happens far more often than you think. For example, Concentric AI’s Data Risk Report analyzed over 500 million unstructured data records from companies in the technology, financial, energy and healthcare sectors and found that one in three files were duplicate or near duplicate.

Let’s explore the benefits of data deduplication and follow up with how Concentric AI can help organizations mitigate risk from duplicate data.

Why is data deduplication important?

Optimized storage utilization: As data storage costs escalate, deduplication offers a reprieve. Organizations can achieve significant storage savings by systematically eliminating redundant data, leading to a more efficient and cost-effective storage infrastructure.

Enhanced data management: Deduplication simplifies the data landscape. With fewer data instances to manage, data retrieval becomes faster, backups are streamlined, and overall data management becomes less daunting.

Cost-effectiveness: Beyond the obvious storage savings, deduplication indirectly leads to reduced power and cooling costs, making it a green initiative. Backup costs can also plummet.

Improved data transfer: With remote and hybrid workplaces now the norm, data often needs to travel across many networks. Deduplication ensures that only essential data travels, leading to quicker transfers, which is especially helpful for cloud migrations and remote backup scenarios.

Security challenges of deduplication and duplicate data

While deduplication offers numerous benefits, it is computationally intensive. Organizations must ensure they have sufficient processing power to handle deduplication without impacting other business operations.

The deduplication process also involves manipulating data, which always carries a risk of data corruption. Ensuring data integrity is paramount, and organizations need robust mechanisms to validate data post-deduplication.

Beyond tangible costs, there are a myriad of security concerns brought about by duplicate data, including:

Overly permissive access: Every duplicate piece of data creates an additional access point that must be secured. The more copies of data that exist, the more entry points there are for potential unauthorized access.

Inconsistent data protection: Duplicate data often resides in different locations, each with its own set of security protocols. This inconsistency can lead to some copies being less secure than others. An attacker only needs to find the weakest link — perhaps a poorly-protected duplicate — to access sensitive data.

Compromised data tracking: With multiple copies scattered across various storage locations, tracking who accessed what data is incredibly difficult and adds to the challenges of maintaining a comprehensive access log.

Insider threat risk: Employees or other insiders might inadvertently gain access to data they shouldn’t see, which can lead to unintentional data leaks or malicious intent.

Challenges in Data Lifecycle Management: Data has a lifecycle that begins with its creation and ends in deletion. Duplicate data complicates this lifecycle, making it difficult to ensure that all copies of a piece of data are deleted or archived when required. This lingering data can become a silent security threat.

How Concentric AI can help with the data deduplication process

Data deduplication is practically impossible without understanding data lineage. Without a solid grasp on data lineage, organizations are essentially addressing data risk blindfolded.

Data lineage refers to the tracking of data as it moves through the various stages of a system or process — from its origin or source to its final destination. Data lineage provides a visual representation of the data’s lifecycle, including where it comes from, how it’s transformed, and where it goes.

With Concentric AI, organizations can make better business decisions around securing their data by understanding data’s entire journey with a clear and comprehensive view of how it is sourced, processed, modified, entitled, and consumed.

Here’s how we track data lineage and manage duplicate data:

Identify sensitive data: Concentric AI’s strength lies in our ability to pinpoint all sensitive data in the cloud, be it intellectual property or regulated data like PII/PCI/PHI. Plus, Semantic Intelligence works without having to set up complex rules or policies.

Transparent data sharing: With Concentric AI, organizations gain clarity on data sharing dynamics. Our solution provides insights into which data is being shared, and, more importantly, with whom – whether it’s internal stakeholders or external entities. This transparency ensures that duplicate data doesn’t inadvertently end up in the wrong hands.

Visual tracking of data lineage: One of the standout features of Concentric AI is our ability to visually trace the lineage of data. Organizations can track the journey of a file or data record, monitoring any changes or moves. This capability extends to duplicate data and data variants, offering a comprehensive view of data’s evolution and distribution.

Address data variants: Beyond exact duplicates, Concentric AI recognizes and manages data variants — pieces that might not be identical but have undergone modifications. Our solution helps organizations in locating all versions of a particular data piece, ensuring consistent permissioning and reducing risk.

Optimize data storage: Concentric AI’s visualization capability identifies older data versions, allowing organizations to move them to secondary storage. Our process reduces risk associated with outdated data and offers significant cost savings by optimizing primary storage usage.

Ensure consistent permissioning: Concentric AI autonomously ensures that semantically similar data, including duplicates and variants, has consistent permissioning and access controls — no matter where it’s located.

Book a demo today to see firsthand — with your own data — how Concentric AI can quickly and easily be deployed to manage and track data duplication in your organization.