How Financial Institutions Unlock More Value from Data with Object Storage

1. Which of the following best describes your organisation’s current use of object storage? [select one option]

We use on-premises object storage
We use object storage across both on-premises and cloud environments
We use cloud-based object storage only
We do not currently use object storage
Not sure

2. Which of the following best describes the maturity of your organisation’s use of object storage? [select one option]

Piloting or early-stage adoption
Used across multiple workloads or teams
Widely used across the organisation

3. What are the primary use cases your organisation uses object storage for today? [select top three]

Regulatory compliance and records retention
Data protection, backup, and disaster recovery
Long-term archive and cold storage
Active archive or a high-value data repository
Data lake or lakehouse architectures
Hybrid cloud and or multicloud workloads
AI /ML (machine learning) and Analytic workloads
Cloud-native or API-driven applications
IoT data storage
Cyber resilience or ransomware concerns

4. Which factors are most important when selecting an object storage platform ? [select top three]

Scalability without sacrificing performance of large data volumes
Governance, security, and compliance capabilities
Ability to support both traditional and emerging workloads
Integration with analytics, AI, and cloud-native platforms
Smart operations: simplicity and high levels of automation
Cost and total cost of ownership
Solution flexibility: mixed workload types, data formats, deployment options, etc.
Data resilience and availability
Sustainability and energy efficiency
Performant – high throughput

5. Which object storage capabilities are most valuable to your organisation today? [select top three]

Data immutability and ransomware protection
Encryption and security controls
Advanced metadata and data classification
S3 or API compatibility
Hybrid and multi-cloud flexibility
Life-cycle management
Policy-driven automation
Integration with analytics and BI tools
Support for modern data formats and frameworks
Operational visibility and monitoring

6. How do you expect the role of object storage to evolve in your organisation over the next 1-2 years? [select all that apply]

Greater role in cyber resilience and business continuity
Increased support for AI, analytics, and data science
Expanded governance, compliance, and sovereignty controls
Broader use across hybrid and multi-cloud environments
Shift from archive-focused to more active revenue generation workloads
Improved performance and accessibility
Enhanced governance and compliance capabilities
No significant change expected

7. What role does object storage currently play in your organisation’s AI or advanced analytics initiatives? [select the most appropriate answer]

No role, and no current plans
No role today, but planned in the near future
Supporting some AI or analytics workloads
Central to our AI or analytics strategy
Unsure

8. Which use cases do you expect object storage to support more actively over the next 1–2 years? [select all that apply]

Advanced analytics and big data
AI and machine learning
Generative or agentic AI
Data lake or lakehouse platforms
Cyber resilience and long-term retention
API-driven or cloud-native applications
Active archive with high-value reusable data repository
Hybrid cloud enablement
No new use cases planned

9. What are your organisation’s top data storage priorities over the next 12 months [select all that apply]

Modernising existing storage platforms to simplify data management and reduce operational complexity
Expanding or introducing object storage
Enabling AI/analytics-ready storage and data platforms Improving cyber resilience and security
Ensuring data sovereignty, regulatory compliance, and policy-driven governance
Managing data growth
Cost reduction and improving storage efficiency at scale
Improving hybrid and cloud integration
Improving data accessibility and reuse across teams, platforms and distributed environments/locations
Improving performance and responsiveness for active and emerging workloads
Centralised data hub or repository (Data Hub Layer - DLH) for governance, reporting, AI/ML and reuse

10. How is object storage currently deployed within your organisation? [select all that apply]

On-premises – as an appliance
On-premises – software defined with bring your own hardware
Private cloud
Public cloud (hyperscaler)
Hybrid (on-premises and public cloud)
Multi-cloud
Consumed as a managed service
Unsure

11. How does data sovereignty influence where and how you run AI workloads using object storage? [select one that best describes your situation]

It does not influence AI workload placement
AI workloads are restricted to specific regions or locations
Training and inference are split across locations due to sovereignty rules
Data must remain on-premises or within private cloud environments
Models are trained centrally, but data remains local
Data sovereignty significantly limits AI workload scalability or performance
Unsure

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