Data quality continues to occupy the attention of management to an extraordinary extent. This is the finding of a new report issued by IDC, "Business Analytics Implementation Challenges - Top 10 Considerations for 2003 and Beyond", which analyses the issue of data quality and its impact on business.
IDC names data quality as the number two issue for companies implementing enterprise-wide business analytics software. Only budget cuts were viewed as a bigger problem for companies implementing enterprise-wide business analytics.
Both IT and corporate management recognise data quality as a problem, according to the survey of 1 648 companies. Fully half of all IT professionals surveyed don`t think they`re sending accurate data to the analytic applications that corporate management is increasingly depending on to run their businesses.
"As a building block for robust business analytics, data quality has long been a neglected area of the market," says Dan Vesset, IDC`s Research Manager for Analytics and Data Warehousing. "It takes considerable discipline and dedicated resources, both of which are in short supply, to overcome ongoing challenges of poor data quality.
"However, not having a data quality initiative is increasingly not an option in an environment demanding continuous productivity gains across all business processes."
Before this IDC report, a study by The Data Warehouse Institute estimated that dirty data costs the world`s businesses $600 billion a year by causing errors and eroding performance.
Ascential Software anticipated dirty data`s implications in early 2002 when it bought data quality software vendor Vality and integrated Vality`s data quality applications into the Ascential Enterprise Integration Suite.
"The phrase `garbage in, garbage out` applies as much to analytics as to any facet of business - if not more so," comments Julian Field, MD of local Ascential Software distributor CenterField Software. "If executives can`t trust the data going into their analytical applications, then the applications are useless as strategic management tools.
"Ascential`s approach has been to tie together data quality and the other essential qualities of enterprise integration - profiling and transformation - into one platform."
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