Data Automation for Enterprise Innovation: 6 Challenges to Solve

Enterprises like yours manage terabytes to petabytes of data daily. Collecting and storing this massive volume of information is already complex. But the real challenge lies deeper. It's in delivering data effectively, securely, and in ways that empower your teams to innovate.

This blog will deep dive into the current state of enterprise data automation and examine the limitations of legacy solutions. Then, we will explore how top-performing organizations approach automation in their industries.

What Is Enterprise Data Automation?

Enterprise data automation encompasses the strategic use of technology to automate data-related tasks within an organization. It aims to streamline data processes, reduce manual effort, and improve efficiency across various business functions. 

Within this broader landscape, test data automation has emerged as a focus area for development teams. It helps ensure your test data is always:

• Compliant with regulations.
• Readily available when needed.
• Perfectly integrated with existing systems.

This approach enables faster development cycles while reducing risk and infrastructure costs.

The Data Automation Reality Check 

Test data delivery becomes a bottleneck. Broken test data processes prevent organizations from achieving true development velocity. Which is why data automation is essential.

Consider SAP environments, where getting a new production dataset once a quarter is considered breakneck speed. But that is still far too slow to:

• Develop new features.
• Resolve issues quickly.
• Beat competitors.

Traditional test datasets are largely static or locked down. Teams can't easily reset, refresh, or share data when needed, limiting their ability to fully test applications.

Despite AI helping write code today, feature delivery may still be bottlenecked by an organizations’ slowest point:  test data delivery.

From Operations-Heavy to Developer-Centric

Data automation requires adopting a "DevOps" mindset. The Ops side can automate data movement. But the real value comes when the Dev side actively interacts with it.

By giving users their own copy of the data and the ability to update, reset, or refresh it at will, organizations empower greater flexibility. This approach maximizes the benefits of shifting left and helps build better applications.

Many traditional solutions focus on basic ETL (Extract, Transform, Load) processes. But they hinder platform engineering due to the speed and cost of these large sets of data. Modern data automation must enable sandbox environments where developers can touch, play with, and customize data themselves.

Enterprise leaders must move beyond the operations-heavy mindset. They need to stop treating data automation as complex, expensive processes. Instead, they should focus on enabling developer self-service and organizational velocity.

6 Key Challenges in Traditional Data Automation

These bottlenecks stem from fundamental limitations in how traditional systems approach data automation. Traditional Extract, Transform, Load (ETL) tools aim to meet enterprise data needs. But they fail to address the growing complexity and requirements of modern businesses. 

Here's where they fall short.

1. Rigid Processes 

Traditional systems function like "copy-and-paste" machines. They lack the flexibility to adapt to nuanced use cases.

Key problems include:

• Businesses struggle to provide data tailored to the developer or project’s specific needs.
• Storage explosion makes data management unsustainable and expensive.
• Applications are evolving rapidly, but data access remains a manual, time-consuming process. 

2. Lack of Scalability 

Dealing with massive datasets is no longer optional. Legacy tools often buckle under pressure. Built for yesterday's data volumes, they lack the distributed processing capabilities and elastic scaling required for modern data workflows. 

The result? Skyrocketing costs, inefficiency, and operational bottlenecks — particularly with PaaS solutions (AWS, Azure, GCP). Companies move to these providers but overspend their budget in a shorter timeframe.

Additional challenges include scaling database automation capabilities across legacy, on-premises, and multicloud environments.

3. Limited Developer Customization 

Application developers and testers face specific challenges with their data needs that traditional tools don't address:

• Shifting to different points in time. An example would be toggling tests back to just before a critical bug occurred to ensure it is fixed.
• Running through test scenarios and sharing the data state with teammates to help triage and confirm issues.
• Automatically grabbing the latest datasets with CI/CD test automation. This is to ensure they're testing against the most current data. 

Many current market approaches offer "what you see is what you get" solutions. Users are often not allowed to truly interact with or manipulate data.

4. High Storage Overheads 

Traditional processes create redundant data copies by extracting full databases for each development, testing, and staging environment. Different teams maintain separate data repositories, creating isolated silos that duplicate the same datasets across departments.

This multiplication of data storage unnecessarily inflates storage costs. The constant movement of these large, redundant datasets also creates slowdowns. 

📘 Related reading: Managing Cloud Costs: How to Get the Balance Right

5. Data Fragmentation

Adding to this complexity is the fragmented nature of an organization’s data landscape. Frequently, companies have chosen a bring-your-own combination approach to solve their business problems: on-premises for cost savings, public clouds for ease of use, or data warehouse platforms for complex analysis. 

Unfortunately for them, each solution has its own interface and management approach, creating a disjointed enterprise strategy for data provisioning and automation. Teams are forced to juggle multiple tools and processes depending on their needs with no commonality.

6. Lack of Unified Visibility

Enterprises often lack unified visibility across diverse platforms and environments. As a result, they struggle to understand and manage their entire data landscape. Organizations need a single pane of glass to monitor and orchestrate data operations, no matter where the data resides or which platforms are used.

Ready to Optimize Your Test Data Management Strategy? 

Download our comprehensive Test Data Management Checklists eBook. Get 4 checklists to evaluate test data management at your organization. 

Ask yourself: 

• Is your data delivery  integrated into automated pipelines?
• Do your developers and testers have cheap, complete, and personal data sandboxes?
• How confident are you that all sensitive data has been redacted in downstream environments? 

Discover other key questions to ask as you assess your strategy's test data processes.

Evaluate Your Test Data Strategy

Traditional vs. Modern Enterprise Data Automation

To understand why traditional approaches fall short, let's compare them to modern solutions.

Traditional ETL tools fall down when making data accessible. Meanwhile, Perforce Delphix enables organizations to leverage their data through three capability tiers.

Modern data automation stands apart from traditional ETL tools in three key ways. These advantages enable enterprises to overcome some of today’s pressing data challenges:

• Sandbox-first approach: Enables true developer experimentation with dynamic, interactive environments. Teams are no longer limited to static data repositories.
• Cost-efficient focused: Virtualization prevents storage explosion and infrastructure bloat to reduce resource costs.
• Enterprise scalability solution: Offers comprehensive scalability that adapts across multicloud environments and diverse database testing needs. Also supports evolving business processes and provides deep insights into data usage patterns.

Transform Data Automation with Perforce Delphix

Traditional test data management creates development bottlenecks through manual processes that take days or even weeks. It also exposes sensitive data and drives up infrastructure costs. 

Perforce Delphix transforms test data automation by delivering compliant, high-quality test data to your dev and QA teams in minutes. Our self-service platform works seamlessly across legacy and cloud infrastructures while maintaining enterprise governance and reducing storage and other resource costs.

Related blog >> What Is Delphix?

Test Data Virtualization Accelerates Development Velocity

Delphix virtualizes production data sources and instantly provisions space-efficient virtual copies. Your developers can access these copies through self-service. Instead of waiting on DBAs for static data, teams get compliant test data with integrated masking for PII and PHI. This accelerates your application releases by 2x and reduces storage footprints by 80%.

Virtual test data copies enable complete developer control through their interface of choice. Your developers can conduct rapid refresh, rewind, and branching without administrative intervention. 

Automated Data Masking That Maintains Compliance and Integrity

Delphix automatically masks sensitive data to comply with GDPR, HIPAA, and CCPA while maintaining referential integrity. This reduces exposed sensitive data and eliminates manual, error-prone data processes.

Proven Delphix Results Across Industries

Higher Education

University of Manchester reduced data refresh times from 16 days to 40 minutes with Delphix’s self-service developer access.

 Read University of Manchester’s Story

Financial Services

Fannie Mae cut data delivery from 6 weeks to 2 days, enabling developer self-service and faster innovation.

Watch Fannie Mae’s Story

Healthcare

Express Scripts virtualized data across mainframe and cloud environments. They saved $1.6M while reducing delivery time from 6 weeks to 2 weeks. 

Watch Express Script’s Story

📘 Related reading: How Dell Flipped Developer Productivity from 20/80 to 80/20

Automated Test Data Management for Faster Innovation

See for yourself how Delphix eliminates development bottlenecks while ensuring data privacy and cutting infrastructure costs. 

Request a no-pressure demo today. 

Get compliant test data in minutes