8 Ways To Ensure Data Quality - InformationWeek

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10/14/2015
07:05 AM
Lisa Morgan
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8 Ways To Ensure Data Quality

The quality of your business decisions is only as good as the quality of the data you use to back them up. Here are some tips to help you determine how reliable your data actually is.
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Embrace The Journey 

There are a lot of things that impact the quality of data throughout its life cycle. Errors can be introduced in the data collection process as the data ages, as it is cleansed and transformed, and while it's being moved among disparate systems. In other words, even accurate data can become inaccurate over time. For example, one bank has spent several years trying to come up with a single view of a customer. This has been complicated by its many acquisitions, as well as by the complex and dynamic nature of its business customers' activities. Regardless of where a company is with its data quality at a given point in time, improving data quality is an ongoing pursuit, not a project that can simply be checked off a list.  
'Organizations get overwhelmed quickly when you talk about data quality. It's a journey, a way of doing business that's going to change things, and it needs to be maintained,' said Angela Fernandez, VP of retail grocery and food service at information standards organization GS1 US. 
A recent test of 24 companies conducted by GS1 US showed that 50% of the data analyzed was inaccurate. One problem with taking a piecemeal approach to data quality is the possibility of introducing errors that affect the system at large. 
(Image: Unsplash via Pixabay)

Embrace The Journey

There are a lot of things that impact the quality of data throughout its life cycle. Errors can be introduced in the data collection process as the data ages, as it is cleansed and transformed, and while it's being moved among disparate systems. In other words, even accurate data can become inaccurate over time. For example, one bank has spent several years trying to come up with a single view of a customer. This has been complicated by its many acquisitions, as well as by the complex and dynamic nature of its business customers' activities. Regardless of where a company is with its data quality at a given point in time, improving data quality is an ongoing pursuit, not a project that can simply be checked off a list.

"Organizations get overwhelmed quickly when you talk about data quality. It's a journey, a way of doing business that's going to change things, and it needs to be maintained," said Angela Fernandez, VP of retail grocery and food service at information standards organization GS1 US.

A recent test of 24 companies conducted by GS1 US showed that 50% of the data analyzed was inaccurate. One problem with taking a piecemeal approach to data quality is the possibility of introducing errors that affect the system at large.

(Image: Unsplash via Pixabay)

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