AI hasn’t just changed how we build — it’s changed how much data we keep.
Across cloud environments, data is constantly created, duplicated, versioned, and retained. Storage scales easily, but ownership doesn’t. Over time, what accumulates isn’t just sensitive data that needs protection — it’s data that no longer serves a purpose.
Stale objects, duplicated files, over-retained versions. Shadow data. And while it may not always be sensitive, it still matters — because every unnecessary object increases both cost and your exposure surface.
Today, we’re introducing Shadow Data Detection in Wiz — a new capability that helps organizations identify and eliminate inefficiently managed data across their cloud environments, reducing both storage spend and unnecessary risk.
Understanding sensitive data remains the foundation of any strong data security program. Organizations need to know what data matters, where it lives, and who can access it.
Shadow data builds on that foundation.
Even with strong visibility into sensitive data, a large portion of the data footprint is often inefficiently managed — duplicated, stale, or simply unnecessary. And whether or not that data is sensitive, it still contributes to both cloud cost and attack surface.
With Shadow Data Detection, Wiz extends DSPM beyond identifying what data is sensitive to also understanding what data is inefficient, unused, or over-retained — so teams can take action.
Across early environments, we’ve already identified over 1 exabyte of data in cloud storage buckets across customers, with a significant portion classified as redundant or stale — translating directly into meaningful cost savings and a reduced exposure footprint. In Wiz’s own environment, this surfaced TBs of redundant data across storage buckets, reinforcing the opportunity to reduce both spend and unnecessary exposure.
The result is clear visibility into what to keep, what to optimize, and what to remove — with measurable impact on both cost and risk.
Shadow Data Detection works as part of the Wiz platform, using the same connectivity already in place across your cloud environments.
Wiz analyzes inventory reports generated directly by cloud providers to evaluate how data is stored and managed, without impacting performance.
From there, it identifies patterns like duplicated objects, excessive versioning, and stale data, surfacing them as Data Findings with clear, actionable context — using both built-in detection logic and the ability for teams to define custom rules based on their own data management policies.
These insights are brought together in a dedicated Shadow Data dashboard, providing a centralized view of inefficient data across your environment — including storage impact, potential cost savings, and areas of unnecessary exposure.
From a high-level view, teams can quickly identify where the biggest opportunities exist and which environments or resources are driving the most inefficiency.
Findings are organized and prioritized based on impact, giving teams a clear view into the most critical inefficiencies across their environment.
Teams can then drill into specific findings to understand exactly what is driving inefficiency and what action should be taken.
This turns data sprawl into something teams can measure, prioritize, and fix — where reducing data directly reduces both cost and exposure.
Shadow data isn’t owned by a single team, which is exactly why it becomes a problem.
Security teams want to reduce unnecessary exposure. Platform teams want to optimize efficiency and cost. Data teams want stronger governance and lifecycle control.
Shadow Data Detection brings these together with a shared, consistent view, so teams can align on where inefficiencies exist, what to prioritize, and how to take action.
Because this is part of the Wiz platform, these insights connect directly to broader context — including access, configuration, and risk — so teams understand not just where data exists, but how it contributes to real exposure.
Shadow Data Detection builds on Wiz’s DSPM foundation, combining inventory-based analysis with data classification and platform-wide context.
This allows organizations to understand sensitive data and unnecessary data side by side, connect findings to real risk across the environment, and take action without introducing new tools or workflows.
It’s not just about reducing what you store — it’s about reducing what you have to secure.
Data growth isn’t slowing down, especially as cloud and AI accelerate how data is created and used. The challenge isn’t just visibility. It’s knowing what should stay, what should go, and what actually matters — for both cost and security.
Shadow Data Detection helps teams take that next step, turning excess data into an opportunity to reduce spend, minimize exposure, and operate with greater clarity.
And as Wiz continues to expand its data security capabilities, this is just the beginning.
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。