Data Analysis & Data Quality
"Poor data quality is the norm rather than the exception, but most organizations are in a state of denial about this issue. " -Gartner Group
Maintaining quality data across the diverse set of transaction, decision, and collaborative processing applications that exist in most organizations today is not a simple task, and the corporate mergers, acquisitions, and reorganizations that occur in many corporates exacerbate the problem. New IT data integration and migration projects designed to provide business users with consistent and clean business information often fail because the IT organization cannot handle, in a cost effective and timely manner, the complex data quality issues involved. These issues frequently arise because the project is undertaken without a clear understanding of the source data that has to be extracted and loaded into the new system.
Data quality is a key success factor in CRM and other Systems Projects. At any given time, according to industry analyst estimates, roughly two-thirds of the Global 2000 are engaged in some form of data migration or data integration project. Concurrently, the same industry analysts’ report that upward of eighty-eight percent of these migration projects either overrun or fail.
They often:
Exceed the planned delivery date
Overrun their budget
Are not used due to a perception of lack of quality data, user confidence goes down.
Are cancelled before they are completed from a combination of the above issues.
At Intricity we believe that if you cannot measure your data quality you cannot manage your data. The process of information quality improvement is one of continuous process improvement of any and all processes, to eliminate the causes of defective data.