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	<description>Data Management Consulting</description>
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		<title>Criteria for True Business Intelligence</title>
		<link>http://infonitive.com/?p=212#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=212#comments</comments>
		<pubDate>Wed, 18 Aug 2010 13:57:37 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Business Intelligence]]></category>

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		<description><![CDATA[The following is an excerpt from Miller et al&#8217;s excellent book on Business Intelligence Competency Centers: (full credit/reference below)     A (business intelligence) platform does not offer true Business Intelligence unless it satisfies all of these criteria:   Breadth: It integrates functions and technologies from across the organization. Truly integrated BI integrates data from [...]]]></description>
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		<title>Data Warehouse Architecture Components and Implementation Options</title>
		<link>http://infonitive.com/?p=205#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=205#comments</comments>
		<pubDate>Thu, 12 Aug 2010 18:22:06 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Data Warehousing]]></category>
		<category><![CDATA[Data Warehousing Basics]]></category>
		<category><![CDATA[Information Architecture]]></category>
		<category><![CDATA[Operational Data Store]]></category>

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		<description><![CDATA[At a high level a generic data warehousing architecture can be said to comprise of the following components: Data Staging Layer (DSL) Operational Data Store (ODS) Data Warehouse (DW, EDW for an Enterprise) Data Marts (DM) Each components functions are follows: Data Staging Layer Decouples extraction processes from data cleansing processes Houses the transformation of [...]]]></description>
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		<title>Evaluation Criteria for Data Quality Platforms and Vendors</title>
		<link>http://infonitive.com/?p=151#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=151#comments</comments>
		<pubDate>Wed, 13 Jan 2010 17:34:02 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Data Quality]]></category>
		<category><![CDATA[Information Architecture]]></category>
		<category><![CDATA[Vendor Evaluation Criteria]]></category>

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		<description><![CDATA[The following criteria should be considered while evaluating vendors and technologies for meeting data quality requirements in an organization: 1. Enterprise Data Quality Framework – Evaluate the degree of effort required to integrate the wide range of functional capabilities into a single architecture and product, so that end users will ideally have a single point of [...]]]></description>
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		<title>In-Memory Analytic Platforms &#8211; The Next Frontier in Business Intelligence</title>
		<link>http://infonitive.com/?p=147#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=147#comments</comments>
		<pubDate>Mon, 26 Oct 2009 18:40:25 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[In-Memory Analytics]]></category>
		<category><![CDATA[Information Strategy]]></category>
		<category><![CDATA[departmental business intelligence]]></category>
		<category><![CDATA[microsoft project gemini]]></category>
		<category><![CDATA[qliktech]]></category>
		<category><![CDATA[qlikview]]></category>
		<category><![CDATA[rapid response business intelligence]]></category>
		<category><![CDATA[spotfire]]></category>
		<category><![CDATA[tibco]]></category>

		<guid isPermaLink="false">http://infonitive.com/?p=147</guid>
		<description><![CDATA[There has been a drive by increasingly technically savvy business teams to perform self-service analysis on the business information that they intimately know in terms of element relationships and business rules. At the same time these business teams do not want to involve their IT counterparts in all steps of the analysis. The primary reason for this [...]]]></description>
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		<title>Data Warehouse &#8211; Analysis &amp; Design</title>
		<link>http://infonitive.com/?p=112#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=112#comments</comments>
		<pubDate>Wed, 16 Sep 2009 19:50:36 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Data Warehousing]]></category>
		<category><![CDATA[Information Strategy]]></category>
		<category><![CDATA[Data Warehouse Architectural Patterns]]></category>

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		<description><![CDATA[The level of aggregation as well as the granularity of details required from management information reports is not known to absolute certainity at the time of analysis and design of a data warehouse. At the same time, it is not optimal to assume that the data warehouse should hold the most granular data available in [...]]]></description>
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		<title>Data Cleansing in Data Warehousing: A Structured Approach</title>
		<link>http://infonitive.com/?p=109#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=109#comments</comments>
		<pubDate>Wed, 22 Jul 2009 04:57:03 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Data Integration]]></category>
		<category><![CDATA[Data Warehousing]]></category>
		<category><![CDATA[Data Warehousing Basics]]></category>
		<category><![CDATA[Data Cleansing]]></category>
		<category><![CDATA[Data Integration Design Patterns]]></category>

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		<description><![CDATA[Data cleaning (also called data cleansing or scrubbing) is especially required when integrating heterogeneous data sources and should be addressed together with schema-related data transformations. In data warehouses, data cleansing is a major part of the so-called ETL process. Data cleansing deals with detecting and removing errors and inconsistencies from data in order to improve [...]]]></description>
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		<title>Challenges of Real Time Data Integration in Data Warehousing</title>
		<link>http://infonitive.com/?p=88#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=88#comments</comments>
		<pubDate>Fri, 19 Jun 2009 15:32:18 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Data Warehousing]]></category>
		<category><![CDATA[Information Architecture]]></category>
		<category><![CDATA[Information Strategy]]></category>
		<category><![CDATA[Active Data Warehousing]]></category>
		<category><![CDATA[Real Time Data Integration]]></category>
		<category><![CDATA[Real Time Data Warehousing]]></category>

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		<description><![CDATA[There is a continual pressure to reduce information latency times in the quest to keep a finger on the pulse of a business. This pressure stems from the rapid changes in the business landscape that have shaped IT strategy over the past four or five years. The move to real time information delivery demands just-in-time [...]]]></description>
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		<title>Data Warehousing: Implementation Strategies for Externally Serviced Data Warehouses</title>
		<link>http://infonitive.com/?p=86#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=86#comments</comments>
		<pubDate>Thu, 18 Jun 2009 17:57:02 +0000</pubDate>
		<dc:creator>Amol Patil</dc:creator>
				<category><![CDATA[Data Warehousing]]></category>
		<category><![CDATA[Business Process Driven Data Warehousing]]></category>
		<category><![CDATA[Data Warehousing Basics]]></category>
		<category><![CDATA[Top Down Data Warehousing]]></category>

		<guid isPermaLink="false">http://infonitive.com/?p=86</guid>
		<description><![CDATA[Companies constantly morph their operational models to find optimal ways of accessing new revenue streams and to cut costs. As a result of these morphing, the underlying technology infrastructure needs to adjust and adapt as well. Mergers and acquisitions, reductions and streamlining, integration with supply chain partners demand constant changes to the data models, often [...]]]></description>
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		<title>Concept of Global Data Codes as an integral part of an MDM solution</title>
		<link>http://infonitive.com/?p=74#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=74#comments</comments>
		<pubDate>Tue, 02 Jun 2009 19:26:54 +0000</pubDate>
		<dc:creator>infonitive</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[Data Integration]]></category>
		<category><![CDATA[Information Strategy]]></category>
		<category><![CDATA[Master Data Management]]></category>

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		<description><![CDATA[An integral part of an MDM solution is the identification of the business critical reference data elements. Such data elements are often embodied as codes in a data model. Those codes that are candidates to be managed via an MDM solution can be termed as global data codes. Global data codes are the key cornerstones [...]]]></description>
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		<title>Advantages of an Effectively Managing Master Data (MDM)</title>
		<link>http://infonitive.com/?p=72#utm_source=feed&amp;utm_medium=feed&amp;utm_campaign=feed</link>
		<comments>http://infonitive.com/?p=72#comments</comments>
		<pubDate>Wed, 27 May 2009 17:04:46 +0000</pubDate>
		<dc:creator>infonitive</dc:creator>
				<category><![CDATA[Master Data Management]]></category>

		<guid isPermaLink="false">http://infonitive.com/?p=72</guid>
		<description><![CDATA[Defining Master Data Master data is a set of core data elements—with their associated hierarchies, attributes, properties, and dimensions—such as customer, product, legal entity, chart of accounts, employee, vendor, market channel, geographic location, etc., that span the enterprise IT systems and drive the business. Master data is not transaction data. Transaction data is information that [...]]]></description>
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