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What is Data Sprawl? Causes, Risks, and Management

Data sprawl refers to the dramatic proliferation of enterprise data across IT environments, which can lead to management challenges and security risks.

6 minutes read

How data sprawl works

Data sprawl refers to the dramatic proliferation of enterprise data across IT environments, which can lead to management challenges and security risks. When data mushrooms and scatters across multiple locations, systems, and devices, IT and security teams find it increasingly difficult to track, manage, and secure it.

Today, the explosion of data collection and generation in modern organizations makes data sprawl an urgent concern. As businesses undergo radical digital transformation journeys, they begin to collect and generate immense volumes of data from heterogeneous sources like internet-of-things (IoT) devices, social media sites, e-commerce transactions, and various digital endpoints (such as employees’ smartphones and laptops). Furthermore, the rise in cloud computing means that businesses often store and manage data across multiple platforms and SaaS architectures, complicating visibility and management. 

According to our research, one out of every five enterprise cloud environments with an internet-facing cloud database or storage bucket features sensitive data like PII, PHI, PCI, and intellectual property. 

Figure 1: Exposed internet-facing data is a significant security and compliance risk

Rising remote work trends also contribute to data sprawl because of the data generated by additional digital identities, personal devices, storage systems, and collaboration software. 

Failure to address data sprawl can have devastating ramifications, including cyberattacks, regulatory compliance failures, management challenges, and inefficient IT workflows and operations. To put it plainly, enterprises need to make the mitigation of data sprawl a priority. 

The common causes of data sprawl 

To successfully address data sprawl, it’s important to know why it occurs. In this section, we’ll explore five reasons why data sprawl is so prevalent. 

  1. Multi-cloud environments: According to the Enterprise Strategy Group, 88% of organization leaders believe using cloud services from multiple providers offers strategic advantages. However, the large-scale adoption of multiple cloud platforms means that enterprise data is increasingly spread across complex and disparate systems. 

  2. Unmonitored data duplication: In complex cloud environments, data duplication could occur due to many reasons, including automated backup mechanisms; negligent users; and suboptimal data management tools, practices, and policies. When data duplication goes unmonitored, the buildup of redundant data can cause numerous problems, such as a loss of data integrity, a rise in cloud storage costs, and a broader attack surface. 

  3. Shadow IT: Shadow IT refers to any IT component that falls outside the stewardship of IT and security teams. A surge in shadow IT results in data sprawl because an enterprise cannot identify data associated with phantom IT assets. Even the simplest unauthorized videoconferencing, file conversion, or graphic design application used for daily tasks can exacerbate data sprawl via shadow data. 

  4. IoT data: Most enterprises use fleets of IoT devices with artificial intelligence–powered analytics to boost their operations. These connected devices constantly capture and generate information, resulting in a steady influx of large volumes of multi-format data. While IoT devices and real-time analytics are essential aspects of modern digital operations, there can be potent security risks associated with data generated from IoT devices. 

  5. Remote work: According to the Pew Research Center, 35% of American workers who can work remotely are doing so full time—and more remote work results in more data. Remote workers typically use many collaboration and communication tools that generate additional data, which often settles in employees’ computers and smartphones. Remote work might be here to stay, but businesses must address the security risks of data sprawl and decentralized data storage. 

Figure 2: Wiz flags unreviewed cloud services to curb shadow IT/data

The risks of data sprawl 

Now that we’ve covered how data sprawl occurs, let’s focus on why it’s so dangerous. Here are the most significant risks associated with data sprawl. 

Increased attack surface

Enterprise data is the primary target for most cybercriminals worldwide. That’s why the simple equation is that more data results in a broader attack surface and a higher probability of cyberattacks. According to The Independent, threat actors caused more than 290 million data leaks in 2023, making it crucial for enterprises to control data sprawl. 

Difficulty in enforcing consistent security policies

Creating and enforcing consistent and standardized security policies is challenging when businesses generate vast volumes of data across a diverse tech stack and labyrinthine multi-cloud and hybrid cloud environments. Without consistent security policies, companies lose control over who has access to what data within their cloud environments, posing a major security and compliance risk. 

Weakened compliance posture

Across industries and geographies, regulators exert immense pressure on organizations to abide by laws and frameworks like GDPR, HIPAA, PCI DSS, and CCPA. Data sprawl can make data sovereignty an overwhelming task. Remember: Even the smallest data privacy violation can mature into huge fines, penalties, and reputational damage. 

Figure 3: Wiz’s data compliance capabilities in action

Inefficient data management and operational overhead

One of the biggest problems of data sprawl is that it transforms a potentially lucrative asset into a financial and operational burden. This is because the uncontrolled proliferation of data across disparate operating systems and cloud storage platforms significantly hinders data discoverability and usability. Data sprawl can also increase data storage and management expenses, which will negatively impact your bottom line. 

The role of data security in addressing data sprawl

Countless data security tools promise to solve the challenge of data sprawl. However, the truth is that disparate, disjointed, and siloed data security solutions can worsen the problem. To successfully control data sprawl, businesses need a robust, comprehensive, and unified data security solution.

Data security posture management (DSPM) is a holistic solution businesses can implement to address data sprawl. With a powerful DSPM solution, enterprises can achieve complete visibility and control over their data, irrespective of the complexity of their cloud environments and operations. 

DSPM solutions ensure that businesses have centralized visibility and traceability of their data. An effective DSPM tool provides a single source of truth about where data is stored, ported, and processed. The best DSPM solutions also ensure the automated discovery of sensitive data, which is a necessity today. 

With DSPM capabilities, organizations can optimize data risk management. For instance, they can continuously monitor their cloud environments for data exposure and misconfigurations and remediate issues before they mature into incidents. Additionally, DSPM ensures improved access governance because enterprises can configure and implement intricate and bulletproof access controls. 

If businesses want a one-stop solution to address data sprawl, DSPM is the way to go. 

Best practices for managing data sprawl

In this section, we'll look at some practical steps and best practices that organizations can implement to minimize data sprawl.

Implement robust data governance frameworks

Data governance frameworks can help businesses break down data silos and unify and orchestrate data management tools, processes, protocols, and practices. With data governance frameworks that blend technical detail with high-level business context and strategy, organizations can implement the ideal data access controls, policies, tools, KPIs, and architectures. Crucially, robust data governance frameworks significantly reduce data privacy violations and compliance failures. 

Regularly audit data storage systems and access controls

Data security should be a proactive and continuous exercise. By regularly analyzing data volumes, warehouses, and public storage buckets (AWS, GCP, and Azure), as well as services like RDS, Azure SQL, and Google Cloud SQL, businesses can continuously optimize access controls and prevent unauthorized access. In other words, regular analysis provides enterprises with a complete understanding of where their data is located and who can access that data.

Encourage the use of approved applications 

To reduce shadow IT and shadow data, it’s important to raise awareness about the risks of using unapproved applications. While sidestepping official IT channels and permissions processes may bring short-term productivity benefits, employees must know the data security implications of those actions. By creating a list of approved IT applications and simplifying permissions processes, enterprises can ensure that their employees don’t contribute to data sprawl. 

Implement tools that monitor data flows in real time

There are multiple benefits of implementing tools to monitor data flows and pipelines at subsecond speeds. For example, with such tools, businesses can know exactly where their data comes from and how it’s managed and leveraged. Monitoring tools also make it possible to identify and remediate inefficient workflows and hidden bottlenecks, and they can help businesses assetize data in previously unexplored ways. In short, complete visibility of data flows ensures a well-oiled and high-performance data ecosystem.

How Wiz can help enterprises control data sprawl 

Wiz DSPM is the ultimate tool for continuously discovering sensitive data, remediating data risks, and gaining a context-rich understanding of potential data-related attack paths, making it the perfect solution for controlling data sprawl. 

With Wiz DSPM, you can discover and classify sensitive data across your cloud environments, conduct the most comprehensive data risk assessments, optimize data governance, right-size data access controls, and benefit from unparalleled data-related threat detection and response capabilities. Furthermore, if your business has mission-critical AI applications, pipelines, and assets, Wiz DSPM comfortably extends into code.

Figure 4: Wiz DSPM extends into code and AI environments

With the centralized visibility and management that Wiz DSPM offers, you’ll be able to make informed decisions about your data and cloud environments. And because Wiz is the first CNAPP solution to weave in robust DSPM capabilities, with Wiz, your IT environments are in the hands of cloud data security pioneers. 

Get a demo now to see how you can keep data sprawl in check.

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