“Think of it like building a house on the foundations of four other homes – each with their own water, electrical, and gas fittings.”
That’s how one CIO recently described her challenge to me. She had just inherited an enterprise data ecosystem built up over two decades – each system with its own access controls, security protocols, and ways of handling permissions. Now she needed to somehow make them all work together as one cohesive infrastructure.
As CEO of Velotix, I hear variations of this “inherited infrastructure” story almost every week. Technology leaders who’ve invested millions in modern data platforms like Snowflake and Databricks, yet still struggle with a fundamental challenge: How do you maintain security and efficiency across generations of different systems while still delivering the performance modern business demands?
Skeletons in the Closet
Let me share a story that brings this challenge into sharp focus. A major transportation company spent $12 million migrating 30,000 databases to the cloud. On paper, everything looked perfect – they had successfully unified their data infrastructure under one roof.
But twenty-three months later, they discovered a skeleton in the closet: They had inadvertently exposed 30 years of applicant data containing sensitive personal information. The solution? They had to deploy 150 consultants for six months just to identify which of their 18.2 million tables contained sensitive data.
This isn’t an isolated incident. Just like in any complex infrastructure project, the challenges often emerge in the day-to-day operations. One financial services organization I worked with was spending 15-20% of their annual Snowflake budget – millions of dollars – just trying to keep everyone playing nicely together.
The Real Impact of Fragmented Access
The problems go deeper than just cost. Consider what happens when a major enterprise onboards new analytics talent:
- Day 1: They get their laptop, email, and basic system access
- Week 1: They’re added to identity management systems and team collaboration tools
- Then… they wait. And wait. Sometimes for 8-12 weeks, just to get access to the data they need to do their job
This delay isn’t just frustrating – it’s expensive. A data scientist earning $150,000 a year costs your organization nearly $25,000 in salary during those weeks of limited productivity. The same story happens when people are changing roles. Multiply that across hundreds of employees, and the hidden costs become staggering. Consider the scale of losses from the delays built into implementing critical initiatives at this scale.
Now for the real terrifying part: Who has access to data that they shouldn’t? What regulatory, reputational, and bottom-line financial risk are you exposed to. There’s nothing less at stake here than the future of your business.
Creating a Modern Data Access Framework with what You Already Have
The solution isn’t ripping out existing systems or adding more complexity. Instead, it’s about building an intelligent layer that works across your current data ecosystem. Here’s how successful organizations are modernizing their approach:
Visibility and Control Across Your Existing Stack
Most enterprises struggle to answer basic questions about their data: Where does sensitive information live? Who has access to it? What are they doing with it? The challenge isn’t just having the answers – it’s having them for every system, from legacy databases to cloud platforms.
The foundation of modern data access is comprehensive visibility:
- Real-time insight into data access across legacy and cloud systems
- Clear view of sensitive data locations in your existing databases
- Unified dashboard to manage permissions for all your data sources
Adaptive Access Control for Your Entire Data Estate
Traditional static permissions break down in modern enterprises where roles and needs constantly change. One financial services firm we worked with needed to manage access for 5,000 users across multiple platforms. Instead of creating thousands of individual credentials, they implemented an adaptive approach:
A single policy layer working across their infrastructure:
- Dynamic permissions that adapt to existing roles and contexts
- Virtual user management to reduce credential sprawl
- Policy-based controls that bridge old and new systems
Intelligent Classification For All Your Data
Manual classification becomes impossible at scale. Like when that transportation company migrated 30,000 databases to the cloud only to later discover years of sensitive data scattered across millions of tables. The solution isn’t more manual work – it’s intelligent automation that can:
- Automatically detect and classify sensitive information
- Apply consistent policies across your entire data estate
- Enable quick response to new compliance requirements
Speed and Self-Service Without Compromising Control
The days of waiting weeks or months for data access are over. Business users expect a path to insights, but traditional approaches force a choice between speed and security. One organization we worked with was taking 8-12 weeks just to provision basic data access to critical data for various AI initiatives, creating a constant bottleneck in business data enablement.
By implementing self-service requesting and AI-driven policy-based insights and recommendations for simple permissions provisioning, they transformed their operation:
- Access requests that took months now resolve in hours
- Teams can securely request and receive data access when they need it
- Permissions automatically adjust as roles change
- All while maintaining security controls and compliance
Continuous Compliance Across All Systems
The days of dreading December audits can end. Modern compliance means having answers before questions are asked. One retail client automated their compliance across dozens of systems, enabling:
- Automatic tracking of access patterns across all platforms
- Instant answers about any system’s compliance status
- Continuous monitoring instead of periodic system-by-system reviews
Each of these elements works with your existing infrastructure, creating a framework that’s both more secure and more efficient than traditional approaches. Most importantly, they work together to solve the fundamental challenge: getting the right data to the right people at the right time, while maintaining visibility and control across your entire data ecosystem – no matter how complex or diverse it may be.
The Access Governance Superhighway
Modern enterprises need a framework where security enables speed and innovation flourishes within clear boundaries. Our most successful customers have mastered this balance, creating environments where teams thrive while maintaining robust protections.
Technology must serve the pace of modern business. When retail analytics teams optimize inventory, they get immediate access to the data they need. When financial services analyze customer behavior, they receive both speed and security by design.
The future of data governance builds highways between systems and teams. These secure, efficient, automated pathways deliver resources exactly when and where they’re needed, while maintaining the controls that keep organizations safe and compliant.
Moving forward requires a fundamental shift in how we approach governance. We must build systems that simultaneously support business agility and protect valuable assets. Data governance can and should become a force multiplier for growth and innovation.
Organizations that embrace this vision – finding ways to automate governance, reduce costs, and accelerate access – will lead in our data-driven future. At Velotix, we’re proud to help our customers achieve exactly this transformation every day.
