IBM to expand data management platform

IBM is working on improvements to its DB2 data management platform, focusing on data warehousing and integration as well as on...

IBM is working on improvements to its DB2 data management platform, focusing on data warehousing and integration as well as on autonomic, or self-managing, computing systems.

The company aims to make the database platform a better resource for integrating data from multiple sources, including information stored in databases from other suppliers.

IBM researchers are also developing additional self-tuning capabilities and working to provide better support for grid computing, in which distributed, heterogeneous systems are linked together to provide a virtual pool of computing resources for running applications.

IBM officials said their data management strategy differs from that of rivals Microsoft and Oracle in that IBM favours a federated approach in which data is stored and accessed from multiple locations, rather than storing all of a companies data in a single, monolithic platform.

One project, codenamed Masala, focuses on information discovery among massive amounts of distributed data, including data not stored in a data warehouse, IBM officials said. For example, a customer service agent seeking information about a caller could have access to information such as e-mails and scanned letters.

IBM's DB2 Information Integrator product already lets businesses access information stored in distributed locations. Masala extends those capabilities to help businesses make better use of the information once it can be accessed centrally.

Masala includes meta data management to track information about the data being integrated and provides faster access to distributed data, allowing businesses to make business decisions based on near-real time information, said Nelson Mattos, IBM distinguished engineer and director of information integration.

Masala could be available to customers for beta testing by the end of the year and could show up in products in 2004, he said.

As part of IBM's autonomic computing initiative, Leo, for Learning Optimiser, is software that learns about relationships between data sets to improve query performance. The software, for example, could prevent redundancies in data queries by learning about correlations in data.

Leo is expected to appear in products in the next 12 to 18 months. It could be used in business intelligence tools for functions such as correlating customers' buying habits.

IBM's autonomic initiative is intended to relieve database administrators of laborious tasks that should be automated, according to IBM.

"We're trying to get rid of the mundane, monotonous, time-consuming stuff and freeing them for what they're really good at," said Patricia Selinger, IBM fellow and vice-president of data management architecture and technology.

IBM also intends its data management platform to be a player in grid computing in the enterprise.

Paul Krill writes for Infoworld

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