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2 - 3 Minute Data Management Videos

4 Aug, 2017

Text and Business Value

04 August, 2017
William H. Inmon
Best Practices

The business value of text is immense, but it is not well understood by most organizations. Analysis of textual data can provide a wide variety of benefits. It is intuitively obvious to many people that there is great business value that can be derived from the analysis of text. But the relationship between business value and the analysis of text is not obvious to everyone. So, in order to explici


3 Jul, 2017

Responsibility for Textual Data

03 July, 2017
William H. Inmon
Best Practices

Textual data is a valuable component for business analytics, but the responsibility for gathering and managing textual data is unclear. Consider textual processing for delivering business value. Where does the end user turn? The end user certainly recognizes the value of textual data. Intuitively the end user knows that there is a wealth of value to be found in text. But the end user also knows th


23 Jun, 2017

Is Text Unstructured?

23 June, 2017
William H. Inmon
Best Practices

Text, the basis of language, can be considered to be unstructured by technicians. However, for others, text and language have a definite structure. It is the simplest of questions. Ask any technician if text – language – is structured or unstructured. If your technician is knowledgeable, the technician will assure you that text is unstructured. In fact the technician will think that you are so


5 Jun, 2017

Managed Metadata Environment (MME): A Complete Walkthrough

05 June, 2017
David Marco
Metadata Management

A managed metadata environment (MME) is the optimal approach to metadata architecture for meeting business and technical requirements Introduction Almost every corporation and government agency has already built, is in the process of building, or is looking to build a Managed Metadata Environment (MME), either as part of a metadata solution or within an enterprise data management initiative.  Man


30 May, 2017

The Third Dimension in Project Management

30 May, 2017
Waffa Karkukly
Project Management

Project management requires the use of a solid framework and an experienced project manager to ensure the success of any project, any size, in any industry Introduction I was hooked on watching the Iron Chef - what got me interested in this show was the project manager in me. Watching these highly skilled chefs be provided with the exact same ingredients, tools, time, and assistance; yet, only one


28 Jan, 2017

Six Myths about Data Quality

28 January, 2017
Steven Sarsfield
Data Quality

Master data management continues to be plagued by poor data quality, costing many organizations time, money, lost customers, lost reputation and inefficiencies. Introduction In several surveys, taken by various research organizations about master data management and data quality, on average, 83% of respondents reported that their organizations have suffered problems due to poor master data. Busin


5 Apr, 2017

Performance Metrics for Data Governance and Data Stewardship

05 April, 2017
Anne Marie Smith, Ph.D.
Data Governance

Metrics and the measurements they create are essential to the success of every data governance program and every data stewardship effort. Introduction Organizations that implement any new initiative must be able to measure its success so the program's leadership can deliver progress reports to stakeholders and sponsors.  Communicating success based on measured facts enables the program to demonst


20 Oct, 2016

The Power of Abstraction in Data Modeling

20 October, 2016
Steve Hoberman
Enterprise Data Modeling

Abstraction is a powerful design tactic for creating flexible, robust and scalable data warehouse data models Introduction I remember meandering through the large galleries of a modern art museum, and stopping in my tracks in front of a very large canvas painted completely red with a single white dot in the center. The title was "City Skyline", and as hard as a squinted or twisted my head, I just


23 Feb, 2017

Data Warehouse Standards

23 February, 2017
Sid Adelman
Data Warehousing

Standards are different from guidelines.  Standards are firm and must be followed.  Successful data warehouses use standards Introduction Many dog owners give their dogs what they consider to be commands.  They are really more like guidelines. ("Boscoe come!… pause, pause, pause…  Well I guess Boscoe is busy with his chewy toy and doesn't want to come just now.") A number of organizations


23 Nov, 2016

Foundations of Metadata Management

23 November, 2016
Anne Marie Smith, Ph.D.
Data Management

Metadata management is one of the foundational components of an enterprise data management initiative.  Many organizations struggle with its incorporation into their data management processes. Introduction Metadata is "data about data."  It is the context for the raw data content.  As stated in the DAMA-DMBOK©, metadata can be thought of with the metaphor of a library's card catalog.  The car



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