The Characteristics of a Modern Data Protection Strategy: Meeting the Data Management Needs of a Digital Enterprise

By Archana Venkatraman, Associate Research Director, Cloud Data Management, IDC Europe

IDC blog sponsored by HPE and Commvault

In the first blog in this series on data protection, (Modern Data Protection Considerations: How Data Protection Needs Are Evolving in the Digital Economy), IDC explained how trends such as hybrid multicloud, cloud-native applications, ransomware and status quo data protection edge initiatives.

Organizations cite data protection, security and compliance as their top concerns with data services. These challenges translate into skyrocketing data protection costs as organizations take a short-term, tactical approach to “fix” legacy data protection environments. IDC research shows that because 2020 has been a peculiar and volatile year, planned IT spending by end users has been disrupted.

Improving data resiliency shouldn’t cost a fortune.

A modern data protection strategy represents a shift from tactical approaches such as point solutions, adding storage capacity, or reducing recovery expectations. Today, this includes transforming the data protection environment with an integrated end-to-end data protection and management platform to meet modern needs.

Multi-layered data protection or a tiered recovery strategy is the hallmark of modern backups – aligning with business resiliency goals with the flexibility to meet the needs of each application and manage a full lifecycle Datas.

A tiered approach includes:

  • Application-consistent snapshots for fast recovery. It is the first line of defense to protect critical data in virtual machines and business applications.

  • An external backup level for additional restore points and no single points of failure. This is the next level for additional resiliency, incremental updates, compliance, and data reuse and recovery.

  • A cost-effective, immutable storage option for long-term retention and archiving. This includes a tape environment to retain backups longer, providing air voids and immutability as an “offsite” copy. It also includes cloud object stores.

In traditional environments, these protection techniques work in isolation and do not take advantage of modern features such as efficient snapshots, software-driven backups, encryption, immutability/write-once, read-many (WORM ), intelligent search and discovery or AI-driven surveillance. to identify and resolve problems in the backup and DR processes.

An integrated data protection platform seamlessly unifies these levels and provides end-to-end data protection, visibility, compliance, and recovery.

A modern, prioritized data protection strategy helps organizations move from infrastructure-focused data protection to application-focused data protection and leverage backup to restore critical services, restore applications business and deliver robust RTOs and RPOs. A modern data protection strategy elevates the value of backup from “insurance” to an engine that meets application availability SLAs and supports a zero data loss strategy.

With high volumes of data being created across core, cloud, and edge, it’s time to take an integrated approach and broaden the scope of data services that include security, compliance, data mobility, and electronic discovery.

IDC believes that by integrating storage environments, data management software platforms, and hardware systems, IT teams can create a continuum of data protection methods needed to provide rapid or granular recovery or mitigate risk. loss of data or reputation as a result of cyberattacks. Organizations are also considering tape as part of their data protection strategy in the face of increasing ransomware attacks and tougher regulations such as GDPR.

Intelligent snapshots, purpose-built backup appliances, scalable backup software, cloud object stores, and tape are all essential for end-to-end data protection.

Of course, the power of tenure cannot be underestimated. Organizations looking to modernize data protection should evaluate new techniques such as migrating data first to a defined large-scale landing zone and then ingesting it into a new environment. This allows pivoting from legacy point solution backup platforms without creating the risk of downtime, data loss, or service interruption.

Modern, integrated data protection also brings huge resiliency benefits, such as:

  • Simplicity. The ability to unifiedly manage the entire data lifecycle, from storage to archiving, eliminates management complexities and improves data visibility for rapid action.

  • Deduplication features to efficiently manage a growing data footprint.

  • Automation to better manage failovers and ensure up-to-date backups in the event of unexpected hardware failures. This brings efficiency and smart resource sourcing, eliminates human error, and frees up staff to work on strategic tasks like governance excellence.

  • Consumption-based pricing. This brings the economy and scale of the cloud to data protection environments with metered, consumption-based pricing.

  • Infrastructure independent data protection management. Data services to manage data in data centers, edge or cloud applications, databases and SaaS environments such as O365 or Salesforce.

  • Inter-cloud data mobility. Ability to move data to ensure hybrid multicloud success.

  • Intelligent policy-based data management. Unified and consistent data management without compromising compliance and privacy needs.

  • Ability to support cloud native environments and aggressive cloud migration strategies. Transparency, robust protection, automation, and policy-driven approaches help reduce risk in cloud and edge migration journeys.

The core value of modern data protection is that it enables data-driven organizations to have greater control over all important data. It’s time to reset data protection architectures to deliver data resiliency, faster backup and recovery, continuous compliance, and 24×7 availability.

In the final blog in this series, we’ll explore best practices for building data resilience, requiring organizations to assess technology as well as skills, risks, and processes.

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