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Displaying 225–240 (of 559)

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Title Popularity * Date
Metadata in the Data Warehouse Summary
Bill Inmon talks about early data warehouses and why metadata was not included in those data warehouses.

Topics: Data Warehousing, Metadata

by Bill Inmon | 0 comments
What Is a Category? Summary
Malcolm Chisholm explains the significance of categories in semantics and ontology, which are becoming increasingly important in data management.

Topics: Business Intelligence

by Malcolm Chisholm | 0 comments
Straightforward Analytics: Establishing Measures Summary
David Loshin explains an important step in achieving straightforward analytics: establishing measures.

Topics: Business Intelligence, Analytics

by David Loshin | 0 comments
Data Management: What is Abstraction? Summary
Malcolm Chisholm discusses three common ways the term "abstraction" is used in data management and how misleading the term can be if not clarified.

Topics: Business Intelligence, Data Modeling and Design, Data Management

by Malcolm Chisholm | 0 comments
What Is Data? Summary
Malcolm Chisholm discusses the origins of data and what the definition of data is in the modern sense.

Topics: Business Intelligence, Data Management

by Malcolm Chisholm | 0 comments
Impacts of Institutionalized Reactivity to Data Errors Summary
David Loshin discusses the negative impact of reacting to data errors instead of preventing them, and how this approach has become all too common in many businesses.

Topics: Information Quality (IQ), Data Quality, Data Management

by David Loshin | 0 comments
Business Intelligence for the Masses Summary
This article examines how "BI for the masses" connects to more specific market trends and reviews results published in The BI Survey 9. Based on over 3000 responses, these survey results provide interesting data on the state of the business intelligence market.

Topics: Business Intelligence

by Barney Finucane | 0 comments
Data Quality: Anticipating Data Errors Summary
Is the need for data quality management eliminated if an organization chooses to address the problem by focusing on fixing the process issues and eliminating the root cause of data issues?

Topics: Information Quality (IQ), Data Quality

by David Loshin | 0 comments
The Rise of Ontology: A Conversation with Felix Van de Maele Summary
Is ontology real or is it destined to disappear in few years? That is just one of the questions addressed in this conversation between Malcolm Chisholm and Felix Van de Maele.

Topics: Information Management, Semantic technologies

by Malcolm Chisholm | 0 comments
Data Use by Analytical Applications: Primary vs. Secondary – Who is #1? Summary
The use of data by downstream analytical applications impacts data management and data architecture. The challenge organizations face is identifying and making accommodations for the information needs of current and future analytical applications.

Topics: Information Management, Data Modeling and Design, Analytics, Data Governance, Data Management

by David Loshin | 0 comments
Is the SDLC Relevant to Data-Centric Projects? Summary
There has been a shift from a process-centric view in application development to a data-centric view. Because so much has changed since the SDLC originated, does it really apply to what is being done today?

Topics: Information Management, Data Management

by Malcolm Chisholm | 0 comments
Computed Attributes, Entity Resolution and Connectivity Hierarchies Summary
David Loshin suggests that it is worth considering the potential of the types of computed or calculated data elements associated with data subject areas that are subjected to entity resolution. The end of the article poses an interesting question, and you’re encouraged to reply.

Topics: Information Management, Master Data Management (MDM), Data Profiling, Data Management, Social Media

by David Loshin | 0 comments
Data Warehousing: Kimball vs. Inmon (By Inmon) Summary
In this article, Bill Inmon compares and contrasts the Inmon and Kimball approaches to data warehousing, highlighting the pros and cons of each approach.

Topics: Data Warehousing
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by Bill Inmon | 0 comments
Data Governance and Data Architecture: Initial Thoughts Summary
Because of the growing interest in enterprise-wide data reuse, there is a need for specific policies for data governance associated with different aspects of data architecture, with the intention of establishing a high level of maturity and capability.

Topics: Data Governance, Information Management, Architecture, Metadata, Master Data Management (MDM)

by David Loshin | 0 comments
Why Venn Diagrams Don't Work for Data Summary
Malcolm Chisholm explains why we need to find techniques that are oriented specifically to data rather than borrowed from other areas of human experience.

Topics: Information Management, Master Data Management (MDM), Data Management

by Malcolm Chisholm | 0 comments

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