Effective data management through active archives

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Download the report to learn how an active archive model serves today's modern and future enterprises.

Effective Data Management Through Active Archives

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Iron Mountain is a co-sponsor of the new 2023 Annual Report from the Active Archive Alliance. The report highlights how active archives position organizations to cost-effectively manage their growing data and address industry pressures while laying a foundation to profit from tomorrow’s opportunities.

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The Active Archive Alliance serves as a vendor-neutral, trusted source for providing end users with technical expertise and guidance to design and implement modern active archive strategies that solve data growth challenges through intelligent data management.


Business and IT leaders well understand the challenges of massive, doubledigit data growth. More devices and applications generate more data from the edge to the public cloud. Copying and replicating data for protection, the need to keep data for longer periods, and even the fear of deleting corporate data add to storage demands. A 40% annual data volume growth rate drives the experience for many industries.1

Key to handling the data growth challenge, especially in the context of flat or slowly growing IT budgets, is effective data management. A working definition of data management involves the processes for gathering and storing data efficiently, securely, and cost-effectively. Without effective data management, data growth overwhelms an organization.

Effective data management brings other crucial benefits. Numerous challenges face IT organizations today, including ransomware threats, budgetary pressures, skill set shortages, and digital transformation. Intelligent, effective data management addresses these issues through cyber resiliency, reducing costs, simplifying data administration, and data accessibility features.

Beyond problems to be solved, data-driven organizations recognize data as a strategic, enterprise asset. In a future world where AI and ML workloads permeate and drive business processes and decision-making at all levels, effective data management becomes imperative. Organizations without intelligent data management processes that feed into business intelligence workloads risk being left behind by their competitors who do.

And this is where the active archive model serves today’s modern and future enterprises.

Active Archiving solves data growth challenges through:

  • An intelligent data management layer to place data where it belongs for cost or performance
  • Adaptability to any storage architecture, media, or protocol
  • Applicability across the entire data lifecycle, from data creation through archiving and eventual purging
  • Security and protection features that safeguard data from threats and risks

An active archive positions organizations to cost-effectively manage their growing data and address industry pressures, while laying a foundation to profit from tomorrow’s opportunities.

“Storing the increasing volumes of data will continue to be one of the priority problems for many companies.”

Thomas Thalmann, CEO, PoINT Software & Systems GmbH


At the center of an active archive resides an intelligent data management system. This software system plays the central role of automatically placing data where it belongs for cost, performance, and workload priorities. Using technologies such as metadata and global namespaces, the data management layer makes data accessible, searchable, and retrievable on whatever storage platform or media it may reside.

Among its many features, the intelligent data management layer adds value by:

  • Automating the decisions for tiering data to long-term storage
  • Automating data management processes such as:
    • Applying data protection and security policies
    • Cleansing data
    • Alerting for anomalous conditions
  • Surveying and analyzing the enterprise data landscape
  • Discovering data for which IT administrators are not aware
  • Presenting visual representations of an organization’s data through charts, graphs, and dashboards for better decision-making
  • Simplifying the skill set needed to oversee and manage large, growing volumes of data

And the data management software does this work in the background without affecting performance.