What Does It Mean to 'Govern Data'?
by Robert S. Seiner
Once you have answered the question of what it means to “govern data,” the next question they will ask is “What is the best way to govern data?” And to that question you can answer … the “Non-Invasive Data Governance”™ approach.

Proven Strategies for Executing Large-Scale Data Modeling Projects
by Satyajeet Dhumne
Satyajeet Dhumne provides an introduction to proven strategies that IT managers can find useful for large-scale data modeling projects.

Dimensions of Data Architecture
by Anupama Nithyanand, S. V. Subrahmanya, P. A. Sundararajan
This article identifies enterprise data architecture dimensions that are used to analyze the requirements, constraints and boundaries in deciding an appropriate solution. We have seen dimensional analysis of data architecture in an earlier article published by TDAN [1]. This article explains in detail the various dimensions used in that reference that could yield richer insights when viewed using these perspectives.

Data Governance and Dancing in the Rain
by Robert S. Seiner
What a Glorious Feeling
This article is a light-hearted approach to convince you to step outside into the storm for a moment, and look for things that you can do right now to put the basic components of the Non-Invasive Data Governance program into place.

The Changing Discipline of Data Modeling
by Dave Wells
New Challenges for Old Modelers
Dave Wells looks at the new data management challenges for data modelers.

Chief Data Officer
by Satyajeet Dhumne
A Career for Data Savvy Business Leaders
Satyajeet highlights the background and skills required for the position of chief data officer.

Dimensional Analysis of Data Architecture
by Anupama Nithyanand, S. V. Subrahmanya, P. A. Sundararajan
In this article, the authors analyze enterprise’s data architecture and obtain intelligent insights to find the best performing solution for a given set of requirements.

Data Governance Value Statements
by Robert S. Seiner
Focus on Cause & Effect
Anybody that has been a consultant or an employee at some point in their life, or anybody who has tried to convince anybody to do something, has used a Value Statement to demonstrate the worthiness of some type of endeavor.

Taking Inventory of the Unstructured World
by Bill Inmon, Krish Krishnan
The corporate document catalog is a good start for getting your hands around all of the important unstructured information in your corporation.

Thoughts on Data Quality
by Craig S. Mullins
Craig Mullins looks at the barriers and inhibitors to data quality.

Data Models and Data Profiling
by Michael Smilg, CDMP, MBA
Complementary Techniques
Data models and data profiling are complementary techniques. Although data models do not tell us the whole truth, profiling the database does not provide the whole truth either. In fact, both may be misleading. However, used together, they can provide better insight into the data.

The Data Governance Test
by Robert S. Seiner
Let's Be Honest!
In this test, statements of data discipline and self-evaluation answers will guide you to build a message that you can convey to your boss, or your boss's boss, or even their boss to let them know that there is an inexpensive, practical and pragmatic approach, a “Non-Invasive Data Governance”™ Approach, to governing your organizational data resources.

Modeling the Blueprint for MDM
by James Parnitzke
Modeling the blueprint for MDM is a key differentiator and the difference between success and failure among major initiatives.

Real Men Don't Read Instructions
by Alex Friedgan, Ph.D.
Alex Friedgan provides a rebuttal to the recent article entitled "Why Data Models Cannot Work."

10 Ways to Save an Hour a Day
by Greg Keller
Greg Keller outlines ten helpful ideas for making more productive, identifying where appropriate tooling or other approaches may be implemented to raise productivity and help automate repetitive tasks.

Earned Value Management
by Michael M. Gorman
This article presents an approach to constructing, producing, and employing earned value management in the accomplishment of database projects. This paper only addresses the earned value for labor. Other types of earned value address materials and facilities.

Link Corporate Policy and Data Design with Decisioning
by Mark Norton
This article discusses the methods which can be used to discover and model decisions in a structured manner, analogous to data normalization. Data and decisions both have important and complementary roles in this decision-centric approach. Data models show the valid states of the system at rest; decision models describe the valid transitions between the states. However, it is the state transitions described by the decision models that generates value for any business, giving the decision model a primacy that is not shared by data.

Architecture Made Easy, Part 4
by Mary Kotch, James Luisi
Finally, The Truth About Metadata: The Business Value and ROI
Maximizing business value requires gathering and analyzing operational metadata from each moment in your operational processes; the gathering of metadata on your operational processes is very much like having radar track everything that is happening in your business operation.

Is a Science of Data Possible?
by Malcolm Chisholm
Malcolm Chisholm presents a case for a science of data.

The Data Stewardship Approach to Data Governance: Part 10
by Robert S. Seiner
The Data Governance Program Team and the Role of IT
This is the tenth and final article in a series describing many of the components of a successful Data Governance program including KIK’s Framework of Roles & Responsibilities. This chapter discusses the Support Level of that Framework – The Data Governance Program Team & The Role of IT.

The CMDB is an Operational Data Store
by Charles Betz
Charles Betz discusses why the CMDB is not a data warehouse, but rather an operational data store.

Why Data Models Cannot Work
by Malcolm Chisholm
Malcolm Chisholm explains why enterprise-level information knowledge management will never be attained by producing a comprehensive set of data models.

The Requirements Bill of Materials: A Walkthrough
by Bill Lewis
Bill Lewis describes a model for application requirements based on a bill-of-materials metamodel.

Governance for Taxonomic Reference Data
by Malcolm Chisholm
Reference data is the Rodney Dangerfield of the data world – it gets no respect. However, it is feared. Malcolm Chisholm explains why.

Agile: The Good News, The Bad News
by Larry Burns
Larry Burns describes Agile Development and discusses the positive advantages of this approach to application development.

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