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IT organizations are well aware that sensitive information resides in corporate databases, but unstructured data--e-mail, Office documents, and other content types--can be just as valuable and need protection. The challenge for IT is that unstructured data is growing at a breakneck pace--a compound annual growth rate of 61%, according to IDC, almost three times the growth rate of structured data. It's also scattered throughout the enterprise: in folders on file servers, on laptops, and tucked inside USB drives. You need a strategy for securing it.
Start by understanding the types of content in your company, and the value it has to the business. If your company handles credit cards, then you automatically think of PCI. Your nightmare is credit card numbers sitting on a file server for anyone to find. If you're in the medical field, HIPAA and patient records are a top concern. Other important data types are customer and employee personal information, intellectual property, and operational data.
These groupings are broad but give you enough to build on. The main idea is to understand the types of data and how you will respond once each type is discovered. Once you compile a basic list, work with representatives from IT, legal, compliance, HR, finance, and business development. They will identify data you've forgotten or didn't know about.
Next, map your data types to a classification and handling policy that outlines how groups of data should be managed. The most common mistake we see when IT groups write these policies is specifying exactly how data should be protected. That approach is inefficient and causes more work for you later. Instead, provide a range of acceptable measures rather than mandates. For example, if your company prefers that data in transit be encrypted using SSLv2, but it also will accept the use of TLS 2.0, put both options in your policy. This makes the policy much more flexible for those implementing the protection. That's critical, because if they can't work with you, they'll work around you.
One last note on data classification policies: They often fail because all documents are tagged as confidential, devaluing the policy. Your classification system should differentiate between valuable information that carries a high level of risk and other information that may be sensitive but carries less risk if exposed or lost.
Searching For Unstructured Data
The next step is finding the data. This can be tricky. You know where it should be stored, but because information is so portable, it has a habit of turning up in unexpected places.
The Agile ArchiveWhen it comes to managing data, donít look at backup and archiving systems as burdens and cost centers. A well-designed archive can enhance data protection and restores, ease search and e-discovery efforts, and save money by intelligently moving data from expensive primary storage systems.
2014 Analytics, BI, and Information Management SurveyITís tried for years to simplify data analytics and business intelligence efforts. Have visual analysis tools and Hadoop and NoSQL databases helped? Respondents to our 2014 InformationWeek Analytics, Business Intelligence, and Information Management Survey have a mixed outlook.