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May 1 2024

Data Speaks for Itself: Is Metadata Data?

Well, of course, metadata is data. Our standard definition explicitly says that metadata is data describing other data. So why would I even ask this question in the article title? The reason I ask it is because we seem to think about and manage metadata as somehow different than “normal data” such as business operations […]

A Step Ahead: IoT Data Characteristics — Seven Vs

IoT (Internet of Things) incorporates many new and innovative technologies, such as sensors, smart devices, machine-to-machine communication, networking, advanced computing, and data analytics. One of the keys in the success of IoT is the data that flows underneath these technologies. Naturally, the IoT sensors and devices generate a huge amount of data automatically and continuously. […]

Crossing the Data Divide: AI Data Assistants — A Data Leader’s Force Multiplier

The focus of my last column, titled Crossing the Data Divide: Data Catalogs and the Generative AI Wave, was on the impact of large language models (LLM) and generative artificial intelligence (AI) and how we disseminate knowledge throughout the enterprise and the future role of the data catalogs. Spoiler alert if you have not read […]

Data Professional Introspective: The Data Management Education Program

In my work with the EDM Council’s Data Management Capability Assessment Model (DCAM) 3.0 development group, we are adding a capability that has remained under the radar in our industry: the responsibility of the Data Management Program to determine concept and knowledge gaps within its staff resources. The organization should then plan, organize, and make […]

All in the Data: A Steward in Need Is a Steward in Deed

You’ve probably heard the expression, “A friend in need is a friend indeed.” For this column, I am going to play with that expression to make a point. Instead of a friend, I will refer to friends as data stewards. Instead of indeed (meaning certainly), I am going to insert a space in the word […]

The Book Look: Cassandra Data Modeling and Schema Design

I love writing this column for TDAN. It lets me discuss what I learned from a newly released data management book. When I publish a book through Technics Publications, I see the manuscript mostly through the eyes of a publisher. But when I write this column, I see the manuscript through the eyes of a […]

Data Is Risky Business: The Opportunity Exists Between Keyboard and Chair

I’m doing some research work for a thing (more on that thing later in the column). My research has had me diving through all the published academic research in the field of data governance (DG) that deals with critical success factors for sustainable (as in: “not falling over and sinking into a swamp with all […]

Legal Issues for Data Professionals: AI Creates Hidden Data and IP Legal Problems

As data has catapulted to a new and valuable business asset class, and as AI is increasingly used in business operations, the use of AI has created hidden data and IP risks. These risks must be identified and then measures must be taken to protect against both a loss of rights and an infringement of […]

Data-Centric: How Big Things Get Done (in IT)

I read “How Big Things Get Done” when it first came out about six months ago.[1] I liked it then. But recently, I read another review of it, and another coin dropped. I’ll let you know what the coin was toward the end of this article, but first I need to give you my own […]

Through the Looking Glass: Data as Code? Or Data as a Code?

Readers of my column know my aversion to buzzwords.[1] I approach the hot catchphrase “Data as Code” with trepidation. Already, we have to name a few: – Infrastructure as Code (with its own acronym, IaC) – Configuration as Code (Config as Code — why not CaC?) – Environment as Code (EaC is not available, as […]

The Art of Lean Governance: Addressing the Elephant in the Room

Hands down one of the most frequent observations when walking the data factory at different clients is the excessive use of spreadsheets for data collection and purification. These spreadsheets are part of a critical data enrichment process for getting reports out the door on time. However, these same spreadsheets represent a significant control problem exposing […]

Eyes on Data: Transforming Data Challenges into Real Progress

In a world increasingly dominated by data, organizations are grappling with the need to effectively manage and harness this valuable asset. And with increased regulations and compliance, opportunities for innovation and AI, digital transformation initiatives, and data-driven decision-making, the demands for accurate, accessible, protected data are increasing exponentially. At the same time, the data management […]

Data Speaks for Itself: Is AI the Cure for Data Curation?

By now, it is clear to everyone that AI, especially generative AI, is the only topic you’re allowed to write about. It seems to have impacted every area of information technology, so, I will try my best to do my part. However, when it comes to data curation and data quality management, there seems to […]

Crossing the Data Divide: Data Catalogs and the Generative AI Wave

The “Tide” of LLMs Has Reached Our Shores As a career data professional and having spent most of the last 10 years with Collibra, Alation, and now as an independent, I’ve come to a somewhat painful, yet exciting realization that large language models (LLM) will completely disrupt and displace data cataloging as we know it! […]

The Book Look: Data Privacy Across Borders

I never realized how complex data privacy rules can be for multinational companies until I read “Data Privacy Across Borders” by Lambert Hogenhout and Amanda Wang. This book not only goes into detail on the privacy regulations from many countries, but it also covers the importance of a global data privacy strategy and the steps […]

All in the Data: The Search for Intelligent Life in Your Organization

An invisible, yet universal, force exists that is shaping the very fabric of data-driven decision-making, data practices, and operational data management functionality. This force is “informal governance,” an astral influence orchestrating the celestial bodies of an organization. Acknowledging the existence of this informal governance marks the launch of a profound journey — a quest for […]

Data Professional Introspective: Demystifying Data Culture

The term “data culture” is frequently used to describe a normative view about how an organization functions (or more precisely, should function) with respect to its data. The term is not particularly well defined, and the notions held about this term can vary significantly. Many data management professionals think of an organization’s data culture as […]

The Data-Centric Revolution: Best Practices and Schools of Ontology Design

I was recently asked to present “Enterprise Ontology Design and Implementation Best Practices” to a group of motivated ontologists and wanna-be ontologists. I was flattered to be asked, but I really had to pause for a bit. First, I’m kind of jaded by the term “best practices.” Usually, it’s just a summary of what everyone […]

Legal Issues for Data Professionals: A New Data Licensing Model

Setting the Stage: Data as a Business Asset This column presents a new model for licensing and sharing data, one that I call the “Decision Rights Data Licensing Model” (or the “Decision Rights Model,” in a shorter form) and one that has been met with acceptance in commercial transactions. The Decision Rights Model addresses current business […]

Data Is Risky Business: Turning Abstract Ethics into Practical Practices

This quarter’s column draws on my keynote for DAMA Calgary’s contribution to DAMA Days Canada last month, which in turn drew on some of the content in the second edition of the “Data Ethics” book I wrote with my colleague Katherine O’Keefe (particularly, Chapter 3 and Chapter 11). My keynote looked at the thorny question […]

Through the Looking Glass: The Unique Identifier of the Rose

I recently taught an online class on BCBS 239: Effective Risk Data Aggregation and Reporting for Risk.net. Preparing the course materials took me back to 2007-2008, when I worked for Merrill Lynch managing the Credit Risk Reporting team. I recall how difficult it was for the banks to provide the aggregated risk data the regulators […]

Data Speaks for Itself: Data Love and Data Limerence

Now that “data” is finally having its day, data topics are blooming like jonquils in March. Data management, data governance, data literacy, data strategy, data analytics, data engineering, data mesh, data fabric, data literacy, and don’t forget data littering. In keeping with this theme, I’d like to propose a couple of new data topics not […]

Eyes on Data: The Right Foundation for Trusted Data and Analytics

Trust. Trust is defined as the assured reliance or belief on the character, ability, strength, or truth of someone or something (Webster’s Dictionary). It’s a term we use often to describe how we feel about the people, the institutions, and the things around us. But I would argue that the term “trust” was used differently […]

The Art of Lean Governance: Walking the Data Factory

The concept of “walking the data factory” drew a great deal of interest during our recent DGPO webinar on data classification as part of a holistic governance program. We discussed ways to connect the stove-piped worlds of data governance and information governance under a common governance classification. There is great power in lean governance when […]

A Step Ahead: Categories – Boon or Bane?

Do you love or hate organizing papers and objects in your home? For those that hate it, why do you hate it? I like the results of organizing: reduction of clutter and ease of finding things. But I hate the process of organizing. The reason usually has to do with the fact that the object […]

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Category Archives: Data Columns