David Hill

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IBM's Broad, Deep Data Protection And Retention Portfolio Strategy

That there is a data explosion is well-known. However, it is not simply an increase in volume for existing data and applications; it also involves new types of data for new applications. The resulting mix does not support all the same data protection and retention requirements businesses are used to, so a comprehensive portfolio of data protection and retention products and services is necessary to cover all requirements. IBM is one vendor that offers such a comprehensive portfolio.

As background to understanding the needs for data protection and retention, let’s examine what is happening in the world of data. Although multiple data types have always existed, not all of them received equal emphasis in business:

  • Structured Data. The first big era in data was around structured data, most notably that inhabiting relational databases. This stage centered on online transaction processing systems (OLTP) applications, which are about automating manual business operational processes. Revenue-generating applications--such as online order entry as well as operational management applications, including supply chain management--are key here. In addition, these include day-to-day operational applications, including accounts receivable, accounts payable and payroll.

    Traditional backup and restore applications have long been applied to these applications as a means of protecting vital corporate assets. Retention policies were not a major focus, as volumes were not oppressive and compliance was not much of an issue. These applications tended to be managed in house (although they could have been outsourced) and related to one company. WAN communications among multiple sites of the same company involved leased lines.

    That was then. Now these applications continue to grow, but life is more complex. Little, if anything, is totally private, as suppliers and customers may have access to some parts of an application, such as a supply chain. Complexity has also increased, as structured data applications may work in conjunction with semi-structured and unstructured data types in a hybrid environment, such as Web revenue-generating applications, as well as some medical applications. And, of course, compliance requirements have become stricter. Structured data is not going away, but now it shares the stage with other types of data.


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