Cloud migration is a central tenet of digital transformation for many organizations looking to modernize their operations. According to a survey by Thomas Reuters, 86% of C-Suite leaders said their organizations are investing in cloud computing as a major part of their transformation strategy, alongside generative AI (79%).
In this post we’ll share our data-safe framework for cloud migration, integrating data discovery and data management in a four-step strategy to ensure sensitive data security throughout the migration process.
Drivers for cloud migration
Moving from on-premises to cloud systems is an attractive proposition for organizations for several reasons, including:
- Scalability/flexibility – Cloud platforms offer easy-to-adjust resources to meet demand, that can be up- and down-scaled according to business requirements
- Cost saving – According to a 2018 IDC report, cloud services offered significant reductions in operational costs (51%). In 2025, cloud cost optimization has become a necessary factor to ensure these efficiencies
- Performance – Cloud providers deliver performance optimized services, improving speed, guaranteed uptime and global access to support a distributed and remote workforce
- Security/compliance – Cloud service providers deliver built-in protections and certifications that many organizations lack resource and/or expertise to manage in-house
- Innovation and integration – The flexibility offered by cloud services can help accelerate development and deployment cycles, enabling organizations to bring products and services to market faster than constrained on-premises networking and development environments. In addition, emerging technology including AI, data analytics and IOT solutions are being developed integration-ready across major cloud services.
Four steps to successful transformation
Plan: Building a secure migration strategy
- Map data flows across systems
- Identify business-critical assets
- Assess regulatory and compliance requirements
Planning and preparation is key to a successful cloud migration. Before making decisions about what cloud services to buy, organizations need to have a clear understanding of the systems, processes, data and users impacted by the change.
It’s crucial to establish visibility of data intended for migration. Mapping data flows, based on both process knowledge and initial discovery scanning, is a foundational step in the migration process.
Adopting a data-led approach enables businesses to more quickly identify the systems and processes associated with the target data, and the users that interact with it.
It also ensures that regulatory and compliance requirements can be established and included in selection criteria and configuration standards.
Scan: Identify and classify sensitive data
- Perform deep discovery scanning of structured and unstructured data
- Classify based on sensitivity and compliance mandates
- Apply risk scoring based on classification and threat exposure
- Clean up ROT data before migrating to save costs and prevent unnecessary transfer of risk to new environments
The scan phase builds on the work done in the previous planning phase activity of data mapping and initial discovery.
In this phase, organizations need to verify data assets across all components that will be migrated to the cloud. This requires deep, full-file scanning to identify sensitive data stored in structured and unstructured formats, in known and unknown locations.
Following discovery scanning, identified data can be classified based on its sensitivity and regulatory status. Classification is an important process that facilitates the operation of effective data security controls, such as data loss prevention (DLP) once the data is transferred to its new environment.
Classification is also a pre-requisite for risk scoring data assets, which can be used to monitor data exposure over time and prioritize remediation efforts.
Finally, cleaning up redundant, obsolete and trivial data (ROT) – data that is no longer required for any business purpose – prior to migration helps prevent unnecessary transfer of risk to new environments and reduces cloud storage costs.
Modernize: Migrate with confidence
- Choose the right cloud architecture (public, private, hybrid, multi-cloud)
- Apply security controls following best practices
- Ensure secure data transfer protocols
A comprehensive understanding of existing infrastructure and the data within it allows organizations to move through the migration phase of the process with confidence – informing migration goals, enabling strategic selection of solutions and services, and facilitating design of the new workload architecture.
Best practice guidelines for cloud security such as the Cloud Controls Matrix (CMM) managed by the Cloud Security Alliance (CSA) encourage developing and maintaining a data inventory, especially of sensitive data, for subsequent control and risk management (DSP-03).
Once the new environment is configured, organizations must ensure the secure transfer of data into the new infrastructure. This process should be continuous throughout the migration process to ensure that data is synchronized between on-premises operations and cloud systems, until full switchover is complete.
Monitor: Manage your cloud data risk
- Ongoing scanning of cloud environments for security and data risk management
- Secure decommissioning of on-premises infrastructure
- Early warning alerting of data exposure, risk identification and mitigation
- Compliance reporting across hybrid and multi-cloud environments
Following switchover, organizations need to shift their focus to establishing a continuous process of data risk monitoring and management. The flexibility of cloud operations offers great opportunities for business. However, without appropriate visibility and oversight, it can introduce additional risks as the ease of creating new environments can result in unauthorized proliferation of data stores.
According to a 2025 report, 31% of organizations lack tools to identify their riskiest data sources across complex hybrid and multi-cloud environments. Meanwhile, 80% of respondents do not feel highly confident in their ability to identify high-risk data sources.
Automated data discovery scanning across cloud services offers an early warning system for sensitive data exposure, risk identification and mitigation.
In addition to monitoring the new environment, organizations need to consider safe and secure decommissioning of their legacy infrastructure, including secure disposal of any sensitive data it holds. Here, device scanning can ensure that assets are ‘clean’ prior to destruction or reuse, minimizing any potential data exposure risk.
Finally, amid a growing regulatory landscape and increasing public awareness of their personal data rights, organizations need to ensure they have tools in place that support compliance across complex digital networks, comprising on-premises, cloud and SaaS infrastructure. While no solution can offer a silver bullet for compliance, continuous data monitoring, risk profiling and reporting provides a baseline for complying with privacy laws and industry standards, identifying critical data assets and providing remediation capabilities.
A data-safe framework for migration with Enterprise Recon
As cloud adoption accelerates – with 82% of c-suite leaders consider digital transformation in their top 10 priorities over the next 18 months – organizations must make sure they adopt a secure, data-safe strategy for migration. The Plan–Scan– Modernize–Monitor framework provides a structured approach to cloud transformation, ensuring that sensitive data is protected at every stage.
Enterprise Recon by Ground Labs is purpose-built to support this framework. It delivers comprehensive data discovery, classification and remediation across both on-premises and cloud environments.
Enterprise Recon offers:
- Unparalleled scanning performance across structured, unstructured and in-memory data
- 300+ preconfigured personal data types for global privacy compliance
- Customizable data patterns and GLASS Studio™ for bespoke discovery needs
- Risk scoring and data access governance capabilities to prioritize remediation and reduce exposure
- Seamless integration with platforms like Microsoft Purview, Power BI and Tableau for advanced analytics and reporting
Enterprise Recon supports on-premises master appliance installation or cloud-hosted deployment on client-managed infrastructure for maximum security and control. Its cloud-native capabilities support all major providers – including AWS, Azure, Google Workspace, Microsoft 365 and more – making it ideal for hybrid and multi-cloud strategies, which now dominate IT architectures.
In 2025, the cloud migration market is projected to reach $0.3 trillion and grow to more than $1 trillion by 2030. While organizations report lower average IT costs, improved scalability and increased uptime following migration, challenges remain. Cloud intrusions are growing at an alarming rate, up 136% in 2025, with data the primary target. Further, breach costs are higher involving cloud infrastructure and take longer to resolve compared. It’s understandable then that executives cite data security in the cloud a key concern.
Enterprise Recon addresses these challenges head-on by offering real-time visibility, targeted remediation and continuous monitoring – ensuring that data remains secure throughout the migration lifecycle and beyond.
To find out how Ground Labs can support your cloud migration strategy, arrange a complimentary data workshop or book a call with one of our experts today.