Why 70% of Your Cloud Data Is Collecting Dust—Clean Up with a Data Digital Twin

Cloud computing has become the backbone of enterprise IT infrastructure, facilitating unprecedented scalability and flexibility. Organizations migrate vast amounts of data to the cloud, though not all data serves a strategic purpose. In fact, as much as 70% of data stored in cloud environments is seldom accessed—essentially collecting digital dust. This underutilization incurs unnecessary costs and complicates data management, hindering operational efficiency.

Addressing this issue requires more than periodic clean-ups; it calls for a strategic approach to continuous data management. This is where the concept of a Data Digital Twin comes into play. By creating a virtual replica of your data infrastructure, a Data Digital Twin allows for real-time monitoring and management, ensuring data remains a robust asset rather than a dormant liability.

Understanding the Impact of Unused Cloud Data

The accumulation of unused data in any environment can impact an organization's bottom line and operational efficacy. Financially, the costs associated with storing inactive or irrelevant data are not trivial.

According to Gartner, enterprises spend more than 50% of their IT budget on storage solutions. When a significant portion of this data serves no active purpose—often tagged as redundant, outdated, or trivial (ROT)—it directly impacts cost efficiency. IDC suggests that identifying and eliminating ROT data, optimizing storage solutions, and implementing data life cycle management practices can lead to cost efficiency. Furthermore, managing this unused data requires additional resources, from administrative oversight to security protocols, all of which add to the overall IT expenditure.

From an operational perspective, having a large volume of dormant data can lead to inefficient data retrieval processes. The presence of redundant or obsolete data can slow down search operations and complicate management tasks, leading to longer response times and decreased productivity. Moreover, the complexity of managing a bloated data environment often leads to a fragmented data landscape where critical data can be overlooked or lost.

Security risks are also heightened in environments with poorly managed data. Unused or forgotten data can easily become a target for cyber threats, especially if it is not regularly reviewed and secured. Compliance risks also arise when data that should have been purged remains in the system, potentially violating data protection regulations and exposing the company to unnecessary litigation risks.

Identifying Unused Data

The first step in addressing unused data is identifying what is active and necessary and what is not. Using Data Digital Twins, we assess data usage and relevance by analyzing access logs and user activity. This helps determine which datasets are in use and which have been untouched for extended periods.

The Data Digital Twin also provides a clear visualization of data interactions and life cycle, making it easier to identify ROT data that might not contribute to business objectives and should be managed appropriately.

Furthermore, regular data reviews and audits facilitated by the Data Digital Twin are critical to maintaining data hygiene. These tools automate and simplify the auditing process, ensuring that data remains relevant to current business needs and that any unnecessary data is promptly dealt with. By leveraging a Data Digital Twin, organizations can ensure ongoing compliance with data governance policies and adapt to regulatory changes more effectively.

Strategies for Data Purging

Effectively managing cloud data not only involves identifying unused data but also implementing strategic measures for its removal or archival. The steps to safely remove or archive unused data include:

1. Classification and Tagging: Categorize data according to its importance, sensitivity, and utility. This step helps determine which data to delete, which to archive, and which to retain for operational or compliance reasons.
2. Data Deletion Protocols: Implement secure deletion practices that ensure data is irrecoverably removed when it is no longer needed. This is particularly crucial for sensitive data that poses a risk if exposed.
3. Archiving Solutions: For data that may be needed in the future or must be retained for compliance reasons, use archiving solutions that store data in a cost-effective, less accessible format.

The role of data governance policies in this process cannot be overstated. These policies provide a framework for deciding what data should be kept, archived, or discarded based on legal, regulatory, and business requirements. Ensuring these policies are adhered to throughout the data life cycle protects the organization from potential legal and financial penalties.

Kellton’s consulting services play a crucial role by helping organizations to regularly update their data governance policies to reflect the evolving regulatory landscape and business needs. Additionally, Kellton’s expertise in automating data management processes reduces the likelihood of human error and educates employees about the importance of data hygiene, further embedding best practices across your teams.

Best practices for data life cycle management include:

• Regularly updating data governance policies to reflect the evolving regulatory landscape and business needs.
• Automating data management processes to reduce the likelihood of human error.
• Educating employees about the importance of data hygiene and their roles in maintaining it.

Leveraging a Data Digital Twin for Ongoing Optimization

A Data Digital Twin is a virtual model of an organization's data assets and their management processes. This technology enables businesses to simulate, predict, and visualize the effects of changes in data management strategies without impacting the actual data environment.

By mirroring the cloud environment, a Data Digital Twin provides a comprehensive view of all data interactions, usage patterns, and efficiencies. This replica allows IT teams to test various data management scenarios, such as compression, deduplication, or tiered storage strategies, to identify the most effective approach for data optimization.

Benefits of a Data Digital Twin include:

• Continuous Monitoring and Analysis: With real-time data about how data is being used and stored, organizations can make immediate adjustments to improve data hygiene and efficiency.
• Cost Optimization: By understanding data storage and usage patterns, companies can optimize their cloud storage costs, reducing expenses associated with underutilized data.
• Enhanced Decision-Making: Data Digital Twins facilitate better decision-making by providing actionable insights into data management practices, helping companies to stay agile and competitive in a data-driven marketplace.

Optimize Cloud Data Management with Data Digital Twins

Effective management of cloud data is essential for operational efficiency, cost reduction, and enhanced security. Often, a significant portion of cloud data remains underutilized, which not only incurs costs but also represents a lost opportunity for operational optimization.

Adopting a Data Digital Twin offers a transformative solution to these challenges. This technology creates a virtual model of your cloud data environment, enabling continuous monitoring, analysis, and optimization of data usage. With a Data Digital Twin, your organization can maintain a cleaner, more efficient, and strategically aligned data environment, ensuring that your data assets deliver substantial value.

Explore the potential of Data Digital Twins and how this innovative approach can revolutionize your data management practices. Kellton leads in deploying these advanced solutions, providing expert guidance to help you effectively manage your data challenges.

Contact us today to schedule a consultation or demonstration. Learn how Kellton’s tailored solutions can enhance your cloud data management, transforming your data into a strategic business asset. Send us a message to discover more about our services and how we can support your journey towards data excellence.