Partner with business decision makers to ensure data quality during the data migration process.
Data migration projects may seem
straightforward, but they often hit snags for a variety of reasons-not the
least of which is data quality.
Bad data can break new applications or systems, according
to experts, and in order to avoid pitfalls associated with it, it's necessary
to loop in business managers to help IT staffers understand and prioritize the
cleansing of mission-critical data.
"What they need to do is analyze the legacy
sources early in the migration effort-measure the levels of quality and
identify the quality flaws that will cause the new system to experience issues,"
said Ted Friedman, an analyst with Gartner. "Then make the decision of
whether to clean up the issues at the legacy sources or while data is being
migrated from old to new."
This requires heavy involvement by the business
and not just its IT department, Friedman continued, explaining that the
business executives know what qualifies as good enough in terms of data
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Studies have found delays to be typical for data
migration projects. A study by research company Bloor released in September
2007 found some 64 percent of all data migration projects come in late and 37
percent come in over budget.
"No company will pay for perfection and you
can't get it anyway-for example, it is estimated that customer data
deteriorates at around 1.5 percent per month [due to] name changes through
marriage, moving house, getting a new cell phone and so on," said Philip
Howard, an analyst with Bloor.
To Tony Sceales, chief technology officer of
Celona Technologies, a successful migration strategy means incorporating a
range of cleansing strategies at different points-some premigration, some
during and some after. In an interview with eWEEK, he said data quality should
be part of an overall data management strategy.
"What's important is to transfer ownership of
the data quality conversation to the business," Sceales said.
Some of the more prominent data quality software
vendors include Informatica, IBM, DataFlux and Business Objects. Stef Damianakis, CEO of
Netrics, which specializes in data matching to catch inconsistencies, said he
recalled his company working on a project with a customer in which only the IT
department-and not the business decision makers-were involved.
"When we identified problems with the data,
IT's response was, 'Can you come and tell the business people for us?' If the
IT people and the business people aren't working together, the project won't go
anywhere. Both skill sets are needed for a migration to be successful," Damianakis