Findings from 110+ data professionals on tool sprawl and stack consolidation
Introduction
Each month, we run a brief survey through our newsletter and social channels to capture what’s top of mind for today’s data teams. The goal is to share actionable benchmarks and peer-driven insights that can help you fine-tune your data stack. These reports aim to reflect the shifting priorities and real-world challenges faced by professionals in engineering, analytics, and operations.
This month, we focused on a growing operational concern: tool sprawl. With many teams expanding their stacks to meet rising data demands, the number of platforms in play, from ingestion and transformation to BI and governance, can quickly become overwhelming.
To better understand how teams are navigating complexity, we sent out a survey to our subscribers with 113 data professionals submitting responses. Here's what they shared.
Why This Survey Matters
The rise of modular, best-in-breed tooling has transformed data engineering, but it has also introduced new challenges. As stacks grow deeper and wider, managing numerous tools often leads to unnecessary overlap, increased maintenance costs, and reduced team velocity.
A 2024 Monte Carlo study found that roughly 70% of data leaders believe their stacks have become too complex, and more than half are planning consolidation efforts within the next year. These findings align with what we're hearing: many teams are rethinking tool portfolios to reduce overhead and improve outcomes.
It's clear that simplification isn't a side project anymore; it's a strategic priority.
Methodology
This report is based on a survey distributed through our newsletter and partner channels, reaching professionals across data engineering, analytics, product, and operations roles.
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Respondents: 113
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Company sizes: Ranging from startups to large enterprises
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Industries: SaaS, fintech, retail, healthcare, manufacturing, and media
Key Takeaways
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62% of teams use over 10 tools in their data stack
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49% describe their stack as fragmented or too complex
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BI and orchestration layers are the most redundant areas
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41% have taken action to consolidate in the past year
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The biggest hurdle to consolidation is lack of internal bandwidth
Tool Volume and Stack Complexity
How many tools are in use?
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How teams describe their stack today:
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Insight
Nearly two-thirds of teams are juggling more than 10 data tools. And half admit their stack has become difficult to manage. The consequences range from slower troubleshooting to unclear ownership due to overlapping systems.
Overlap and Redundancy
Where are teams seeing the most overlap?
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Insight
BI and orchestration layers are the most common areas of redundancy, often stemming from a history of adding tools over time. It's not unusual to manage dbt, Airflow, custom scripts, and multiple analytics platforms simultaneously.
Team Sentiment on Tool Count
How do teams feel about the number of tools they manage?
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Insight
Three out of four respondents feel they're managing more tools than necessary. This suggests that while tooling enables capabilities, it doesn't always increase efficiency. Each new tool adds configuration, monitoring, and support overhead.
What Teams Are Doing About It
Consolidation actions taken in the past year:
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Insight
Despite broad awareness of tool sprawl, only 41% of teams have taken action. The rest face internal barriers or are simply in evaluation mode.
What’s Getting in the Way?
Top blockers to tool consolidation:
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Insight
Consolidating tools often requires coordination across engineering, ops, finance, and leadership. Execution stalls not due to lack of awareness, but because change requires time, attention, and alignment.
Final Thoughts
The modern data stack was once the bright, shiny answer to breaking free from legacy systems, celebrated for its flexibility and the freedom to choose best-in-class tools at every layer. But that same flexibility has given rise to unchecked complexity.
In large enterprises, especially, the situation has become increasingly fragmented. Different teams and lines of business often use overlapping tools, sometimes even the same tools, configured differently, resulting in duplicated effort, increased costs, and slower execution. Toolsets have become bloated, difficult to manage, and harder to unify across the organization.
The value of the modern data stack remains clear, but realizing that value at scale requires a shift in mindset. The path forward lies in simplifying: reducing tool sprawl, minimizing fragmentation, and leaning into platforms that offer both breadth and cohesion. Flexibility is still key, but cohesion is what enables clarity, speed, and sustainable growth.
Teams prioritizing consolidation will likely gain faster onboarding, better cost visibility, and stronger data governance, without sacrificing agility.
About Integrate.io
Integrate.io helps data teams streamline operations by automating ingestion, transformation, and orchestration of your data from various sources to your destination. Fewer tools, less maintenance, and more time for delivering insights.
Ready to simplify your stack? Request a demo!
