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	<title>Netrics HD</title>
	<link>http://www.netrics.com/blog</link>
	<description>A High Definition View of the Business and Technology of Data Matching</description>
	<lastBuildDate>Mon, 30 Nov 2009 18:24:46 +0000</lastBuildDate>
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		<title>Data Quality Enlightenment</title>
		<description><![CDATA[After years of neglect, data quality is slowly moving to the forefront of business technology as both a discipline and a thriving industry.
However, given data quality license revenues are estimated at a relatively minuscule $400 million for 2009 (compared to $17 billion for DBMS license revenues), data quality is not quite center stage yet.
Therefore, in [...]]]></description>
		<link>http://www.netrics.com/blog/data-quality-enlightenment/</link>
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		<title>Data: Transparency vs. Quality?</title>
		<description><![CDATA[In my previous post The Challenges of Data Transparency, I discussed the news about the data preparation for Recovery.gov regarding how state and local recipients are spending federal stimulus money.
In the post, I talked about the juxtaposition of data transparency and data quality, and how although missing or incomplete data is a common problem, completeness [...]]]></description>
		<link>http://www.netrics.com/blog/data-transparency-vs-quality/</link>
			</item>
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		<title>HITECH Challenges</title>
		<description><![CDATA[In his recent Internet Evolution article Stimulus Plan Moves Healthcare Tech Center Stage, John Soat reported on the challenges facing healthcare providers under the section of the United States federal stimulus bill known as the Health Information Technology for Economic and Clinical Health (HITECH) Act, which is intended to jumpstart the use of digital technology [...]]]></description>
		<link>http://www.netrics.com/blog/hitech-challenges/</link>
			</item>
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		<title>Service-Oriented is Future-Oriented</title>
		<description><![CDATA[In his recent ebizQ.net article SOA, Phase 2: Toward a Loosely Coupled World, Joe McKendrick declared:
“I am a passionate believer in the power of technology, as an enabler of entrepreneurship and organizational transformation. I have long advocated flattening the organizational hierarchy, and pushing decision-making down to the managers and employees who deal with customers and [...]]]></description>
		<link>http://www.netrics.com/blog/service-oriented-is-future-oriented/</link>
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		<title>The Chaos Theory of Data Quality</title>
		<description><![CDATA[“One of those issues that is always a source of frustration in the enterprise,” explained Michael Vizard in his recent IT Business Edge blog post, The Never Ending War for Data Quality, “is the quality of the data we spend so much time and money processing.  The quest to make sure we have high quality [...]]]></description>
		<link>http://www.netrics.com/blog/the-chaos-theory-of-data-quality/</link>
			</item>
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		<title>The API and the Innovation of Enterprise Applications</title>
		<description><![CDATA[“One of the bigger trends to come down the pike lately,” explained Jim Ericson in his recent Information Management blog post The API is the New Network, “is the proliferation of Web-based application programming interfaces, or APIs, and how network traffic is growing exponentially through APIs.”
More and more organizations continue to look to innovations in [...]]]></description>
		<link>http://www.netrics.com/blog/the-api-and-the-innovation-of-enterprise-applications/</link>
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		<title>MDM: “Golden” Repository or “Fool&#8217;s Gold”</title>
		<description><![CDATA[Master Data Management (MDM) is the logical extension of a 20 year evolution in data management practice.  The strategic goal for MDM is to provide a single, “golden” repository of mission-critical data that assures all systems, organizations, and users are getting consistent, accurate information to support their needs.
Today, a number of vendors are positioning themselves [...]]]></description>
		<link>http://www.netrics.com/blog/mdm-golden-repository-or-fools-gold/</link>
			</item>
	<item>
		<title>Data Sherpas Needed</title>
		<description><![CDATA[In the recent New York Times article Training to Climb an Everest of Digital Data, Ashlee Vance reported on the challenges associated with managing – and deriving value from – massive repositories of data.
“Researchers and workers in fields as diverse as bio-technology, astronomy and computer science,” reports Vance, “will soon find themselves overwhelmed with information.  [...]]]></description>
		<link>http://www.netrics.com/blog/data-sherpas-needed/</link>
			</item>
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		<title>The Challenges of Data Transparency</title>
		<description><![CDATA[In the recent Federal Computer Week article Stimulus spenders race to the finish line, Alice Lipowicz reported on the efforts of state and local recipients to prepare detailed reports on how they are spending federal stimulus money.
Among the common concerns cited in the article was dealing with the sheer volume of data, and more importantly, [...]]]></description>
		<link>http://www.netrics.com/blog/the-challenges-of-data-transparency/</link>
			</item>
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		<title>Fundamental Requirements for Data Matching Models</title>
		<description><![CDATA[Data matching determines whether two or more records should be linked, are duplicates, or represent the same entity.  There are many different approaches to data matching.  In Machine Learning, advanced mathematical techniques are used to construct a data matching model for the way that humans perceive similarity.
In this post, I want to discuss what any [...]]]></description>
		<link>http://www.netrics.com/blog/fundamental-requirements-for-data-matching-models/</link>
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