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Principles and Rules Listing Page

Data Quality is not Perfect Quality

This is the standard definition of Quality. Data Quality has to be optimum and not perfect. While a customer will always demand perfect quality, the same has to be balanced between the level of quality and cost of quality.
 
This page of 'Principles and Rules' is linked to:  Data Quality,



Fixing Data quality standards and associated risk interpretation is a difficult and constantly revised decision. There are no fixed ground rules, however the data related to regulatory compliance, financial exposure and possible legal exposure is always the first priority.

Business owners and IT owners of the data should carefully look at the quality thresh-holds and the actions that are needed to be taken on a certain instances of data quality issues. For example if there is a mismatch between the agent commission amounts across the agent management system and GL systems by 2%, should we stop the processing and re-run it or should we just give a post-facto warning.

Another way to establish the standards apart from home-work, is to look at the industry bench-marks.


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Relevant Links to this page
TOPIC - Root Cause of Data Quality Issues → Impact of Bad Data Quality → Principles & Rules → Data Quality is a subject of business ownership and not of IT-ownership → Principles & Rules → Don't create a hype on Data Quality Program. → Principles & Rules → Sponsor for a Data Quality Program → Practice Techniques → Business Case for Data Quality → Principles & Rules → Engage the Vendors in Data Quality Program → Practice Techniques → How to get more data along with Sales leads → Practice Techniques → Ask for dates instead of number of years → Principles & Rules → How to Maximize the effectiveness of Data Stewardship → Practice Techniques → Field Tips Series#1- Data Mapping and Assessment → Principles & Rules → Data Management Standards for Data Entities will be a mix of collaboration and top-down → Principles & Rules → Data Management standards for data entities are not only for IT systems → Principles & Rules → Cascade your standards and guidelines to business partners and Vendors → Principles & Rules → Data quality assurance and control guidelines are no-brainer. Publish one immediately and evolve thereafter. → 
 
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Relevant links to this page
Root Cause of Data Quality Issues
Impact of Bad Data Quality
Data Quality is a subject of business ownership and not of IT-ownership
Don't create a hype on Data Quality Program.
Sponsor for a Data Quality Program
Business Case for Data Quality
Engage the Vendors in Data Quality Program
How to get more data along with Sales leads
Ask for dates instead of number of years
How to Maximize the effectiveness of Data Stewardship
Field Tips Series#1- Data Mapping and Assessment
Data Management Standards for Data Entities will be a mix of collaboration and top-down
Data Management standards for data entities are not only for IT systems
Cascade your standards and guidelines to business partners and Vendors
Data quality assurance and control guidelines are no-brainer. Publish one immediately and evolve thereafter.
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