What is “workspace sprawl”?
Workspace sprawl refers to the uncontrolled proliferation of Power BI workspaces within an organization. Every new initiative, every new project, every new team creates “its own” workspace, often without a naming convention, without a clearly identified owner, and without a clean-up process when the project ends or the team is reorganized.
The phenomenon has a name in IT literature (by analogy with the “server sprawl” or “SaaS sprawl” seen in other tool categories), because it follows a very similar growth pattern.
How it happens
Power BI was designed for self-service: in many organizations, a large number of users can create a workspace in a few seconds, without prior approval from an administrator. This simplicity, a key driver of the tool’s rapid adoption, becomes a governance problem as soon as the company goes beyond a few dozen active users and several business departments.
Visible symptoms
- Dozens or even hundreds of workspaces, a significant share of which (often 20 to 40% among our clients) no longer has an identifiable active owner in the company.
- Unclear workspace names (“Test”, “Copy of…”, “Project 2023”, “Sandbox JM”) that make searching by name ineffective.
- Several workspaces containing near-identical reports, created independently by different teams unaware of previous versions.
- Rising processing costs linked to refreshing all the accumulated artifacts: saturation of Fabric or Premium capacities, increased consumption on the data platforms queried (Snowflake, Databricks, etc.).
- Workspaces created for a one-off need (a project, an audit, a POC) and never archived once that need has gone.
Why it is a governance problem, not just a tidiness issue
Beyond the purely cosmetic or organizational aspect, workspace sprawl directly complicates three critical dimensions.
Security
It is impossible to know who has access to what without exploring each workspace individually. This problem is covered in our article on auditing Power BI access. The more workspaces there are, the larger the potential attack surface, and the more forgotten access silently accumulates.
Data quality
The multiplication of sources of truth mechanically creates inconsistencies between reports, a phenomenon discussed in our article on governance warning signs.
Costs
Every workspace hosting active artifacts generates costs, whether or not these artifacts are actually used. First, there are scheduled refreshes and data processing that no longer serve anyone, on a Fabric or Premium capacity but also on the data platforms queried at each run (Snowflake, Databricks or any pay-as-you-go warehouse).
Above all, there are human costs: time spent refactoring, modifying or troubleshooting reports and models whose usefulness is no longer proven. On a fixed-size capacity, these unnecessary processes do not
increase the bill immediately, but they eventually saturate it and push towards a higher tier.
A 4-step method to regain control
Step 1: Map the existing environment
Get a complete, up-to-date inventory of all workspaces, with their declared owner, creation date, last activity and the number of artifacts they contain. This map is an essential prerequisite (see our article on Power BI inventory for the detailed method).
Step 2: Identify duplicates and dormant workspaces
Cross-referencing the inventory with actual usage data (and not just the creation date) makes it possible to distinguish active, legitimate workspaces from dormant environments that have not been viewed for several months. Functional duplicates (several workspaces addressing a similar need) can be spotted by comparing report names and the data sources used across workspaces.
Step 3: Define a naming and lifecycle policy
A simple but systematically applied policy radically changes the course of sprawl: who can create a workspace (with or without administrator approval), which naming convention to adopt (a prefix per department, for example), and above all which archiving process to trigger automatically after a defined period of inactivity (for example 90 days without views or changes).
Step 4: Set up continuous monitoring
A big one-off clean-up, however thorough, becomes outdated within a few months if no continuous monitoring follows. Workspace sprawl is never solved for good by a single action: it is an ongoing phenomenon that requires constant vigilance, with alerts as soon as a new workspace is created or a potential duplicate appears.
Key figure
Among our clients who have rationalized their Power BI workspaces, it is not unusual to find that 30 to 40% of existing workspaces have not been viewed for more than six months: a volume that often represents significant cost reduction potential.
Frequently asked questions
Should users be prevented from creating workspaces freely?
This is generally not recommended: it slows down the adoption and agility that make Power BI so powerful. A more effective approach is to allow free creation but put in place monitoring and a clear lifecycle (automatic archiving after inactivity), rather than restricting upfront.
How do you identify the real owner of an old workspace?
First cross-check the workspace’s declared Admin role with the company’s active HR directory. When no active Admin is identified, the workspace should not be deleted outright: you need to find the business unit it serves, talk to the manager concerned and assess together whether to keep it, assign a new owner or archive it.
Does workspace sprawl have a direct impact on costs?
Yes, directly or indirectly: every unnecessary refresh consumes resources on the Fabric or Premium capacity when there is one, and on the data platforms queried (Snowflake, Databricks…), which are often billed on usage. Added to this, in all cases, is the time teams spend maintaining artifacts whose actual usage has not been verified.
See also: “Power BI inventory” to map your existing environment, and “Reducing Power BI costs” to turn this clean-up into measurable savings.
