Managed Metadata Environment (MME): A Complete Walkthrough

05 June, 2017

David Marco

Metadata Management

New

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

The Third Dimension in Project Management

30 May, 2017

Waffa Karkukly

Project Management

New

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

Six Myths about Data Quality

28 January, 2017

Steven Sarsfield

Data Quality

New

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

Performance Metrics for Data Governance and Data Stewardship

05 April, 2017

Anne Marie Smith, Ph.D.

Data Governance

New

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

The Power of Abstraction in Data Modeling

20 October, 2016

Steve Hoberman

Enterprise Data Modeling

New

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

Data Warehouse Standards

23 February, 2017

Sid Adelman

Data Warehousing

New

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

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

Foundations of Enterprise Data Management

20 October, 2013

David P. Marco

Data Management

Enterprise Data Management is the global function that facilitates the management of data as a valuable asset of an enterprise.  Its components align to provide the capabilities to manage data as an organization resource. Introduction Enterprise Data Management (EDM) is the global function that facilitates the management of data as a valuable asset of an enterprise.  As defined in the DAMA Inter

Logical and Physical Data Modeling Overview

20 October, 2016

Anne Marie Smith, Ph.D.

Data Architecture

Logical and physical data modeling are essential components of every organization's enterprise data architecture, and should form the foundation of every database design.  Standard techniques for logical and physical data modeling enable consistent development and usability.  Even though the concept of data modeling has been around for a long time, in many organizations it is interpreted differe

Increasing the Business Value of Business Intelligence

01 October, 2010

Mark Mosely

Data Warehousing / Business Intelligence / Analytics

Organizations can find increased value in business intelligence and analytics efforts through the use of various data delivery strategies. Introduction Like many organizations, your company probably has invested significant time, effort, and money into establishing your data warehousing and business intelligence environment.  You’ve built the databases and the ETL programs to move, clean and in