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Data classification fueled by e-discovery, storage tiering

What can data classification do for you? Maybe more than you think. The newest data classification tools offer more automation and drill-down functions than ever before. Fueled by the rise in e-discovery requests, and the increased use of storage tiering as a way of dealing with an explosion of data, the data classification market is getting a makeover. Find out what every storage professional should know about today's data classification market in this SearchStorage.com tutorial.

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Data classification for storage managers
Data classification best practices

Data classification for storage managers

The information lifecycle management (ILM) buzz during the last few years spawned a rash of data classification products that aimed to locate and identify files and documents, categorize them with greater precision based on policies and business value, and, in some cases, search or index the information and assist in migrating lower priority data to less expensive storage.

But as the initial noise died down, some of those vendors dissolved or were acquired, and many of those left standing recognized a need to focus their attention on the markets where they apply their technology.

"What we discovered over time is that customers need to be able to take some action on the data, not just find it," said Karthik Kannan, vice president of marketing and business development at Kazeon Systems Inc. "Nobody wants to do data classification just for the sake of it. It has to be coupled with a strong business reason."

→ Editor's Tip: Read this article to learn more about the changing data classification market.

Data classification best practices

Data classification benefits from a team effort, whether the exercise is associated with a storage tiering project to manage resources more effectively, an e-discovery initiative in response to a lawsuit or some other result.

What follow is a list of best practices to help storage managers establish data classification strategies.

1. Identify the sources and types of data across your organization. Before classifying data and figuring out which information should be retained, backed up, archived or deleted, it helps to know the applications the organization uses, the value they represent, the types of data they produce and access patterns.

2. Establish data categories before making technology decisions. What data constitutes a record, and do records need to be stored separately? Do intellectual property documents need to be grouped together? Determining the criteria by which you need to classify information will have an impact on a host of other decisions, so it pays to nail down categories first.

→ Editor's Tip: Learn more about data classification best practices.

This was first published in April 2009