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Garbage in, Garbage out

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CIOL Bureau
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Research shows corporations make decisions based on remarkably inaccurate or incomplete data, a bad habit that's a leading cause of the failure of high-profile and high-cost IT projects such as business intelligence and customer relationship management deployments, said an online report.

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According to Ted Friedman, principal analyst with Gartner most enterprises do not understand the impact of poor data quality. Bad or incomplete data can have an enormous impact on major IT initiatives, such as business intelligence (BI) and customer relationship management (CRM) roll-outs, Friedman claimed.

The problem lies either with the way in which data is collected or the way it is made available to the concerned users. In most cases the data is not in sync across the enterprise.

According to his research, a quarter of the Fortune 1000 companies is working with poor-quality data.

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Friedman is not only talking about corrupted data -- although that can be a part of the problem -- when he points to the pitiful state of data. Instead, data quality is defined by a number of components, ranging from consistency --whether the data is identical when stored in multiple locations -- to accuracy and relevance. If there's data, but it's not relevant to the process or project at hand, it's worthless. Said the online report.

Another part of this problem is the way data is collected. Poor data quality can also arise when data acquisition exercise is carried out through IT. Here the problem arises because there are no proper guidelines about what data has to be collected.

BI is the best example of 'garbage in, garbage out,' said Friedman. Companies using BI software for making strategic decisions can land themselves into major trouble because of bad data.

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Most of the companies today are facing this problem and are looking for solutions that can help them optimize their operations. Synchronization will become an even bigger issue for businesses in the near future as they struggle to integrate the enormous amounts of data gathered from RFID projects. The answer to all this is Data Synchronization.

Many companies are being forced to address data quality because of stricter regulations such as Sarbanes-Oxley, which has requirements that demand the data collected be relevant.

Friedman harped that people, process and technology have to join hands to find a solution to this. It is more of a business problem than an IT problem, and rolling out new technology may not fix this problem. It will just be a short-term solution.

















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