8 Ways To Ensure Data Quality - InformationWeek

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Data Management // Big Data Analytics
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10/14/2015
07:05 AM
Lisa Morgan
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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(Image: maxkabakov/iStockphoto)

(Image: maxkabakov/iStockphoto)

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shamika
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shamika,
User Rank: Ninja
10/23/2015 | 7:38:44 AM
Re: You cannot improve what you don't measure
Maintaining data quality is an important aspect. In my opinion both IT and the respective business has to play a major role in getting it sorted.
jagibbons
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jagibbons,
User Rank: Ninja
10/19/2015 | 7:37:58 PM
Re: You cannot improve what you don't measure
Ownership is a challenge. In my experience, there's a lot of individuals or departments at the ends of the spectrum, i.e. I own it or I want you to own it, but not a lot of cooperation in determining who should own the data and who can best utilize it for the good of the company.
jchimni
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jchimni,
User Rank: Apprentice
10/19/2015 | 5:24:58 PM
Re: You cannot improve what you don't measure
Thanks Jagibbons!

Agreed! Adding to the complixity is the the fact that, in most organizations, ownership of data is also not clear.  

Data is one of the key casues of delay in most of the M&A initiatives as well. 
jagibbons
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jagibbons,
User Rank: Ninja
10/19/2015 | 4:44:54 PM
Re: You cannot improve what you don't measure
Excellent points, jchimni. Data is so misunderstood. Users don't know where it came from, who's worked with it or even what is means to a business decision.
jchimni
50%
50%
jchimni,
User Rank: Apprentice
10/15/2015 | 1:37:01 AM
You cannot improve what you don't measure
There is a fundamental reason why companies have bad data - there are no readily available applications that help measure the quality of data and prevent it from degrading. Tools are available to build those applications, not the applications. This industry is at the same stage where ERPs were in the early eighty's - building custom ERP solutions. We need to start controlling the quality when data is being created.  Need to follow the 1-10-100 rule.

New generation applications are required which will help address this problem. Current MDM/MDG solutions are not sufficient. We need to bring together three components that link with master data:

 - Data quality metrics

 - Business rules engine and industry specific rules repository

 - Quality analytics, exception management and business impact analytics  

This problem has not been solved for 30 years and cannot be solved with the existing solutions.
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