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Topic starter
10/06/2026 9:47 pm
TL;DR: Data sprawl emerges when SaaS data, access, and ownership spread across disconnected tools, making visibility, compliance, and retention harder to govern, according to Zluri. For IAM and IGA teams, the real issue is not storage volume alone but the absence of lifecycle controls that keep data and access aligned.
NHIMG editorial — based on content published by Zluri: IT Teams How to Manage Data Sprawl in 2026: 5 Efficient Ways
By the numbers:
- Only 5.7% of organisations have full visibility into their service accounts.
Questions worth separating out
Q: How should security teams manage data sprawl in SaaS environments?
A: Start by mapping where data is stored, who owns it, and which identities can still reach it.
Q: Why does SaaS sprawl make governance and compliance harder?
A: SaaS sprawl creates multiple independent storage and access decisions across departments, which breaks visibility and weakens auditability.
Q: What breaks when data classification is not tied to access control?
A: Classification without access control becomes a label with no enforcement.
Practitioner guidance
- Build a SaaS-to-data inventory List every business application that stores customer, employee, or operational data, then assign a system owner and data owner to each one.
- Tie classification to access review When a dataset is marked sensitive or regulated, require a corresponding review of user, vendor, and service-account access before the label is treated as complete.
- Separate active, archived, and redundant data Define distinct storage locations or policies for live work, completed work, and stale copies so old files do not remain in high-access collaboration areas.
What's in the full article
Zluri's full article covers the operational detail this post intentionally leaves for the source:
- Five-step data sprawl workflow mapped to practical SaaS management tasks
- Examples of centralized data storage and cloud retrieval patterns across teams
- Detailed walkthrough of Zluri's discovery, duplicate app removal, and access restriction features
- Vendor management workflow examples for consolidating SaaS ownership and reducing duplicate data
👉 Read Zluri's full guide to managing data sprawl across SaaS apps →
Data sprawl in SaaS apps: what IAM teams are missing?
Explore further
12/06/2026 6:40 am
Data sprawl is really access sprawl with a storage layer attached. The article frames the problem as information growth, but the governance failure is broader: once SaaS data fragments, identity controls fragment with it. That creates separate decision planes for data location, access rights, and retention, which is why visibility collapses before anyone notices a breach. Practitioners should treat sprawl as an identity governance problem, not a storage housekeeping issue.
A few things that frame the scale:
- 79% of organisations have experienced secrets leaks, with 77% of these incidents resulting in tangible damage, according to Ultimate Guide to NHIs.
- Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
A question worth separating out:
Q: How do lifecycle controls reduce data sprawl over time?
A: Lifecycle controls keep data moving from active use to archive or deletion according to policy, instead of leaving copies in collaboration tools indefinitely. That reduces clutter, limits the amount of sensitive data under daily access, and makes retention decisions auditable. The goal is not only cleaner storage. It is narrower exposure.
👉 Read our full editorial: Data sprawl in SaaS environments is an identity governance problem
