Data Hierarchy Over Time

By Virginia Citrano  |  Posted 2008-01-30 Email Print this article Print
 
 
 
 
 
 
 

Information lifecycle management helps companies handle the data deluge by providing a framework for classifying stored information, finding the right storage technology, creating retention guidelines and managing costs.

 

Data Hierarchy Over Time

Beth Cohen, director of operations for data protection and storage consultancy Broadleaf Services, in Burlington, Mass., says ILM combines library science’s traditional understanding of how information changes relevance over time with the storage industry’s expertise in hierarchical data retrieval.

“ILM offers a different paradigm for companies wrestling with a tidal wave of data,” says Cohen, whose clients include a company trying to archive more than three million Microsoft PowerPoint slides.

The initial emphasis of ILM was on finding a framework for data classification; that is where the Storage Networking Industry Association’s road map still starts. But classifying data and assigning a life expectancy to its usefulness is hard work—harder still if the tools don’t match the task.

“The amount of unstructured data has been growing by leaps and bounds, and the tools were just not keeping up,” Cohen says.

To keep themselves from being overwhelmed by the data tidal wave, many organizations merely bulked up the beachhead with more storage gear. However, in a report issued earlier this summer, analyst firm Gartner predicted that, by 2010, rising costs for storage media, energy and storage facilities will compel companies “to abandon the axiom that it is easier to add storage than to craft an ILM strategy.”

The Gartner report focused on companies in the h1ealth care industry, but its author, Barry Runyon, says its conclusions hold true for other industries as well. Runyon’s recommendations include:

  • Slow storage growth by improving overall use.
  • Initiate a project to discover, identify and classify critical enterprise data, both structured and unstructured.
  • Establish performance and recovery objectives for each data category. 
  • Establish formal data-retention schedules.
  • Deploy a storage resource management tool.
  • Implement a tiered-storage infrastructure with at least three tiers.

For many companies, the genesis of their ILM strategy lies in regulatory compliance. Regulators demand that certain categories of information be kept for set periods in a certain way. The companies they regulate must comply. These organizations have learned the hard way that not having a data-retention policy—or failing to follow an existing policy to the letter—can be highly damaging.

Financial-services companies, for example, were among the first to get a broad set of targeted ILM tools because they faced so many mandates on their data. The finance industry’s e-mail archiving tools are robust enough to collect missives sent from a wide variety of communications devices, and can sock away instant messaging chats, too. These tools are now making their way out to a broader audience that includes both enterprises and their legal counsel.

“Attorney review time is the most expensive part of discovery,” says Brad Harris, director of product management at electronic discovery services provider Fios. “So it’s good to have a tool that makes that more efficient.” Harris’ common-sense tips: Move information off desktops into shared storage, use a content management system and take full advantage of its metadata tagging capabilities, dispose of what you don’t need and, above all, stick with the company’s ILM plan.

“A lot of companies talk about having retention policies, but nobody follows [them],” Harris says.



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