Storage Switzerland recently wrote about the need for enterprises to move away from using backup processes for long-term data retention use cases. Backup implementations add value in providing high availability and fast (or instant) recovery of the enterprise’s most critical data, but it is not feasible from a budget perspective to store all copy data in this manner. This creates the need for more sophisticated data tiering, management and protection. In this installment, we will explore more deeply the additional value beyond cost savings that a modernized data management and protection approach can bring to the enterprise.
Complying with New Privacy Regulations
Stricter data privacy regulations including the European Union’s (EU’s) General Data Protection Regulation (GDPR) and California’s Consumer Privacy Act (CCPA) require enterprises to have greater visibility into and more granular control over the data they are storing. Storage professionals should consider a data management solution that includes policy modeling, to better understand what data will be impacted by regulatory compliance, and how that data will be impacted.
Additionally, a data management solution that provides holistic visibility into the types of data being stored, data access maps, and immutable history into administrator and user activities can help the enterprise to respond more confidently and more quickly to eDiscovery requests. Along this vein, a solution that inspects content for data quality, including version history and access controls, as well as for unusual data activity and audit history on files can help not only to ensure compliance but also to more quickly identify and react to malware (including ransomware) and malicious user activity. Storing data in a write-once-read-many (WORM) format can furthermore assist through making data immutable, but retention periods and redundancy need to be managed.
Compliance regulations such as GDPR and CCPA add the requirement for businesses to be able to remove a user’s data at the user’s request (“the right to be forgotten”). Adhering to these requirements necessitates a shift away from volume-level backup jobs that are common to most backup software, in favor of a solution that uses smart indexing and that can be granularly searched. Especially important is the ability to identify and tag files that include personally identifiable information (PII) such as credit card information. Once tagged, IT can then employ retention and sharing policies, and it can more quickly identify, delete and anonymize individual files with PII.
Data Repurposing, Mining and Monetization
Beyond storing data to comply with retention requirements, modern businesses are looking to store and harness data for competitive advantage, via analytics, artificial intelligence (AI) and machine learning (ML). Serving these workloads first requires a data management solution that can automatically capture large pools of high-velocity data in real time. To avoid breaking the bank, this data must be actively tiered to lower-cost storage as it ages but the data management solution must also be able to quickly recall files to faster-performing storage to support analytics, AI and ML queries.
In the compliance- and insights-driven era, data management is critical. Ineffectual data management practices add costs through improper storage infrastructure provisioning, while also adding day-to-day complexities that cost valuable staffing resources. Arguably even more strategically, it also risks the organization’s ability to comply with privacy regulations and to turn AI and ML queries into value-add business insights in a timely manner.
Our next installment will discuss in more detail the hallmarks of modern data management and protection architectures. In the meantime, watch our on demand webinar “Complete Your Cloud Transformation – Store Your Data in The Cloud” and receive a copy of latest eBook, “Understanding the Difference Between Data Protection and Data Management.”
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