Data archiving is one of those seemingly boring yet indispensable activities that can help your organization enormously if done in a smart way and hinder your business if neglected.
Here’s a review of some of the basics.
What is the definition of data archiving?
Data archiving is the migration of data from active production systems or outdated legacy applications to an archiving platform. It typically applies to data that is static, meaning data that is no longer updated or no longer changes. And while you might think that static information should naturally be destroyed because it seems like it’s at the end of its lifecycle, that’s not the case. Static content is frequently retained for compliance or strategic business reasons, such as analytics.
What’s the difference between data archiving and long-term storage?
At its core, the difference between data archiving and long-term data storage is the expectation for instant data retrieval. Archiving platforms, like OpenText InfoArchive, provide a way to easily search and quickly retrieve archived data. This is because there’s still some active intent for accessing archived data, such as responding to audits. In contrast, long-term storage is used for data for which there are few expectations for instant data retrieval, and so it tends to be a “file and forget” tool.
What is active archiving and how is it different from other data archiving?
There are two general scenarios for archiving data: active archiving and archiving data from legacy systems. Both should be part of a larger data or information governance strategy that primarily aims to support data management requirements and reduce overall data management and storage costs.
Active archiving refers to the identification of information on production systems that reaches a point of inactivity—when it effectively becomes static—and moving it automatically to an archive. In contrast, archiving data from outdated, unsupported, legacy systems is done to “turn off” these systems while providing ongoing access to and safeguarding of their data.
In either context, data is migrated from production or legacy systems through an extract, transform, and load (ETL) process to the consolidated archiving platform. The archiving platform, then, retains the data until an identified purge or destroy date, when the information reaches the end of its lifecycle.
Often, organizations archive data to meet retention requirements, but this in itself isn’t usually a compelling enough reason. After all, you could just leave static data on your production systems or let it gather dust on your aging applications that have been replaced by newer systems. So, what are the compelling reasons for archiving your data?
- Compliance: Any organization that has to respond to audits—and that wants to avoid costly fines—should archive data, especially that which resides on legacy systems. If static data subject to compliance requirements is scattered across multiple legacy systems, it’s not easy to respond to audits. This increases risk. Or if you’ve updated a Human Resources, Accounting, ERP, electronic medical record system, or other application, you likely have legacy data on the original system. If only one person in your organization was familiar with that application and has left the business, how easy is it to get the information you need in order to respond in a timely and effective way to audits? By moving your data to a single and more modern archive, you can make it easy for the appropriate individuals to access and search legacy information quickly, making it much easier to support the audit process.
- Cost Takeout: Some organizations continue to keep static data on primary Tier 1 storage even after it has reached a stage where it is static (no longer changes). Moving static information off of tier 1 storage reduces primary storage costs. The larger the organization and the greater the amount of information generated, the greater the savings from data archiving can be. Moreover, many organizations continue to pay maintenance and licensing fees for aging systems just to keep access to the data that resides on them (for compliance or analytics purposes). For large organizations, these fees can amount to millions of dollars over several years. By moving information from those legacy systems to a consolidated archiving platform, you can “turn off” those legacy systems and recoup the maintenance and licensing fees that can be invested in more strategic areas of the business.
- IT Simplification: Reducing primary storage demands and eliminating outdated, unsupported legacy systems helps clean up your IT infrastructure.
- Big Data Analytics: With the enormous volume of information being generated every day, it can be a gold mine for getting insights into customers, products and ways to enhance your business. However, if information is trapped in silos on outdated systems, you can’t get to it. Moving this data to a consolidated archive frees information from those silos, adding a valuable dimension to your analytics.
Organizations in highly regulated industries or that are subject to data regulations (such as HIPAA, the Health Insurance Portability and Accountability Act, the Dodd–Frank Wall Street Reform and Consumer Protection Act, or Sarbanes-Oxley and others in the U.S., or in Europe MiFID, the Markets in Financial Instruments Directive (MiFID) or the new General Data Protection Regulation) archive data. Similarly, any organization that has growing volumes of information and that needs to proactively manage storage resources and costs, or that pursues comprehensive business analytics strategies, archives data.
In addition, organizations commonly archive data in conjunction with the following strategic IT or business initiatives:
- IT transformation, such as hybrid cloud or IT-as-a-Service
- Application Rationalization / Modernization
- Data Center Consolidation / Migration
- Enterprise Application Implementation / Rollout
- Mergers & Acquisitions
- Business Shutdown or Sale
- Corporate Compliance / Information Risk Management Programs
Who’s responsible for data archiving?
Data archiving responsibilities are shared primarily by the Chief Data Officer, Chief Compliance Officer, Chief Information Officer, and their teams. Their responsibilities intersect at the points of information governance (an organization’s strategy for managing information throughout its lifecycle to meet internal and external requirements), information volume (understanding how much structured and unstructured data you have and how much is being generated from which sources), and information management (the execution of your information management strategy, or where the best place is to put information as it travels throughout its lifecycle, and the processes and systems required to support that journey).
While one individual might champion data archiving as a pillar of your information management strategy, the stronger the cross-functional partnership in building and supporting it, the more successful you will be.
Where can you learn more about data archiving?
Gartner’s Market Guide to Structured Data Archiving and Application Retirement describes data archiving, trends, and vendors that offer data archiving platforms. Each of the vendors also provides information about how they approach data archiving.
Flatirons specializes in data archiving using the InfoArchive platform from OpenText. We’ve worked with healthcare providers, banks, insurance companies, aerospace manufacturers, electronics manufacturers, public agencies, and other organizations to help them develop and implement data archiving strategies to support their information management requirements. Visit our resources to learn more.