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Abstract:
Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy.
Looking beyond general approaches and company policies that set expectations and establish data management procedures, we
will explore applications and tools that help reduce the negat (...)
Excerpt related to
data quality process:
Data quality has direct consequences on a company's bottom-line and its customer relationship management (CRM) strategy.
Looking beyond general ap...
Published:
2004-03-08
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Abstract:
Successful e-commerce relies on intelligible, trustworthy content. To achieve this, companies need a complete solution at
their back- and front-ends, so they can harness and leverage their data and maximize the return on their e-commerce investment. (...)
Excerpt related to
data quality process:
Successful e-commerce relies on intelligible, trustworthy content. To achieve this, companies need a complete solution at
their back- and front-e...
Published:
2003-01-04
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Abstract:
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing
a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed. (...)
Excerpt related to
data quality process:
... from a multitude of sources makes its way to an enterprise data warehouse or data
marts, a data quality framework creates a screening process that measures
the ...
Published:
2009-07-17
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Abstract:
Most enterprises fight fires with axes, fire hoses, trucks, and hordes of firemen, but the CDQM approach is a smoke detector.
It’s far less expensive to put a fire out when it’s just smoldering, rather than to extinguish a blazing house fire and then
remodel the entire house. (...)
Excerpt related to
data quality process:
... customers. Having a continuous data quality tool in place during this
ETL process would prevent this data nightmare from occurring. ...
Published:
2002-10-18
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Abstract:
Successful e-commerce relies on intelligible, trustworthy content. To achieve this, companies need a complete solution at
their back- and front-ends, so they can harness and leverage their data and maximize the return on their e-commerce investment. (...)
Excerpt related to
data quality process:
Successful e-commerce relies on intelligible, trustworthy content. To achieve this, companies need a complete solution at
their back- and front-e...
Published:
2003-01-04
-
Abstract:
Most enterprises fight fires with axes, fire hoses, trucks, and hordes of firemen, but the CDQM approach is a smoke detector.
It’s far less expensive to put a fire out when it’s just smoldering, rather than to extinguish a blazing house fire and then
remodel the entire house. (...)
Excerpt related to
data quality process:
... customers. Having a continuous data quality tool in place during this
ETL process would prevent this data nightmare from occurring. ...
Published:
2002-10-18
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Abstract:
There are two types of extract transform and load (ETL) vendors. Business intelligence (BI) vendors integrate ETL functionality
into their overall BI framework, while best-of-breed data integration vendors, who provide enhanced ETL functionality, have
an increased focus on data cleansing and integrity. (...)
Excerpt related to
data quality process:
There are two types of extract transform and load (ETL) vendors. Business intelligence (BI) vendors integrate ETL functionality
into their overall...
Published:
2006-03-07
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Abstract:
No matter how well an enterprise implements a CRM, ERP, SCM, Business Intelligence, or Data Warehouse project, poor data
quality can destroy its utility and cost real dollars. (...)
Excerpt related to
data quality process:
No matter how well an enterprise implements a CRM, ERP, SCM, Business Intelligence, or Data Warehouse project, poor data quality
can destroy its u...
Published:
2002-10-17
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Abstract:
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience.
Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework
to manage data on a continuous basis. (...)
Excerpt related to
data quality process:
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience.
Implementing CDI...
Published:
2009-09-11
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Abstract:
No matter how well an enterprise implements a CRM, ERP, SCM, Business Intelligence, or Data Warehouse project, poor data
quality can destroy its utility and cost real dollars. (...)
Excerpt related to
data quality process:
No matter how well an enterprise implements a CRM, ERP, SCM, Business Intelligence, or Data Warehouse project, poor data quality
can destroy its u...
Published:
2002-10-17
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Abstract:
The 2002 Sarbanes-Oxley Act (SOX) has affected organizations, their data, and their reporting processes, putting a strain
on how their financials are managed. Business intelligence solutions provide answers to these issues, allowing organizations
to address SOX compliancy. (...)
Excerpt related to
data quality process:
The 2002 Sarbanes-Oxley Act (SOX) has affected organizations, their data, and their reporting processes, putting a strain
on how their financials ...
Published:
2006-04-06
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Abstract:
Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than
depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches
include an "open book" policy, which includes pub (...)
Excerpt related to
data quality process:
... It was a circuitous process, but DataStage remains ... good way to
encourage higher quality software when ... see Evoke Software Releases Axio Data
Integration Product ...
Published:
2001-02-15
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Abstract:
IQMS appears to be raising the competitive bar for quality management among its ERP competition with a single database software
solution and seamless ERP systems access. (...)
Excerpt related to
data quality process:
IQMS appears to be raising the competitive bar for quality management among its ERP competition with a single database software
solution and seaml...
Published:
2005-04-07
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Abstract:
Quality does not start at the receiving dock and end at the shipping dock. The focus on the supply chain demands that the
quality department be involved from the beginning to the end of the supply chain. (...)
Excerpt related to
data quality process:
Quality does not start at the receiving dock and end at the shipping dock. The focus on the supply chain demands that the
quality department be in...
Published:
2006-01-20
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Abstract:
Product, project, process, and people represent the four areas of PLM analytics that may help PLM user organizations develop
better products, improve the product development process, increase operational efficiency, and better measure employee performance,
respectively. (...)
Excerpt related to
data quality process:
Product, project, process, and people represent the four areas of PLM analytics that may help PLM user organizations develop
better products, impr...
Published:
2009-11-27
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Abstract:
If you run one hundred batches, some will be great, some will be terrible. But what causes some to be great and some to be
terrible? Knowing the answer to that question can mean no more terrible batches, many more great ones, and making more money. (...)
Excerpt related to
data quality process:
... data. For example, for a single batch comprised of ten ingredients, we can have ten
or more quality parameters for each ingredient plus perhaps a dozen process ...
Published:
2004-08-30
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Abstract:
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for
data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating,
and querying a data warehouse typically carries an ext (...)
Excerpt related to
data quality process:
... others to match the rule. This process is also referred to as "data
scrubbing" or "data quality assurance". It can be an extremely ...
Published:
2002-08-18
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Abstract:
It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be
able to discover valuable data. Consequently, data mining technology becomes important. Here is a framework to help understand
the data mining process. (...)
Excerpt related to
data quality process:
It is now imperative that businesses be prudent. With rising volumes of data, traditional analytical techniques may not be
able to discover valuab...
Published:
2009-06-19
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Abstract:
Legacy data can be lethal to your expensive new application – two case studies and some practical recommendations. (...)
Excerpt related to
data quality process:
Legacy data can be lethal to your expensive new application – two case studies and some practical recommendations.
Published:
2002-08-23
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Abstract:
There is a perception that if business users are given access to enterprise databases and raw query tools, they will create
havoc in the system, which is a possibility—unless the business intelligence (BI) product developer understands the potential
problem and addresses it as a business-critical facto (...)
Excerpt related to
data quality process:
There is a perception that if business users are given access to enterprise databases and raw query tools, they will create
havoc in the system, w...
Published:
2005-07-15