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Oct 2 2024

Data Leader’s Playbook for Data Mapping

I’ve been thinking a lot about data mapping lately. I know, weird, right? With analytics, AI, cloud, etc., why would someone do that? What’s even stranger is that I’ve been thinking about its impact on data leaders. For clarity’s sake, I’m not talking about geographic maps with data points, I’m referring to the process of […]

Legal Issues for Data Professionals: Current Leading U.S. AI Laws

There is no nationwide federal law in the U.S. that specifically regulates the development, deployment, and use of AI in the private sector. (This contrasts with AI use in U.S. federal agencies, as discussed below.) This absence of such a federal law contrasts with the recently enacted AU AI law. Instead, in the U.S., there […]

The Book Look: AI Governance

Technics Publications has started publishing a line of Data-Driven AI books, and one of the first books in this series is “AI Governance” by Dr. Darryl J Carlton. The goal of the book in one sentence is to enable the reader to gain the knowledge and tools to effectively govern and oversee the use 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 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 […]

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 […]

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 […]

The Data-Centric Revolution: “RDF is Too Hard”

We hear this a lot. We hear it from very smart people. Just the other day we heard someone say they had tried RDF twice at previous companies and it failed both times. (RDF stands for Resource Description Framework,[1] which is an open standard underlying many graph databases). It’s hard to convince someone like that […]

Eyes on Data: Importance of Data Governance When Implementing AI/ML

Artificial Intelligence (AI), Machine Learning (ML) and Large Language Models (LLM) have turned the world on its head. From finance to manufacturing to pharmaceuticals to retail, every industry is jumping on the AI/ML bandwagon. And for good reason. AI/ML has the ability to improve efficiency, drive automation, and shorten delivery cycles. AI/ML applications can absorb […]

A Step Ahead: Data in Support of (Zero) Trust

Over the past year, the conversations around Zero Trust have begun to accelerate. Much of the discussion is akin to data mesh and data fabric where business owners and management are hearing the term and asking what a Zero Trust product is. The term is also permeating data professionals’ conversations. This article provides a brief overview of […]

Resilience in Data Services Through Mitigation and Prevention

If your company works with data, then you need to work on securing it. When it’s lost or stolen by hackers, it can mean serious trouble for your organization and your bottom line. You must understand what’s at stake, how the data can be easily lost, the steps you can take today to mitigate the […]

All in the Data: Becoming a CDO When There is No Role

I work with a lot of organizations that do not (yet) have a person in the role of Chief Data Officer (CDO) or Chief Data and Analytics Officer (CDAO). I also work with a significant number of people in these organizations who have the desire to be elevated into one of these roles. The latter […]

Data Professional Introspective: Conducting a DCAM Assessment

My company led a Data Management Assessment for a government agency this spring, using the Data Management Capability Assessment Model (DCAM), and delivered the final report at the end of May. In my last column comparing the DCAM to the DMM, I said that I’d share my observations with you so that you can get […]

Crossing the Data Divide: Closing Gaps in Perception of Data as Corporate Asset

It’s my great pleasure and honor to begin as a columnist for TDAN.com. TDAN.com has a long and distinguished record of giving voice to ideas in the data space and I will do my best to continue that tradition. The Crossing the Data Divide column will be aimed at data leaders. That is to say, […]

Data is Risky Business: Data Ethics and Governance in the Age of LLMs

In the last few months, we have seen the wave of Artificial Intelligence break on the shores of wide-scale business adoption and mainstream media coverage of Large Language Models, most famously ChatGPT. While these technologies have immense potential to benefit organisations and society, they also bring with them an equal, if not greater, risk of […]

Eyes on Data: An Approach to Measure Data ROI

Justifying any significant business investment is challenging. For data managers, the struggle is especially familiar. The difficulty is convincing decision makers to invest in data when measures of data’s value either do not exist or feel too ambiguous to estimate. As digital transformation accelerates, interest in frameworks for linking data to monetary measures grows.Connecting data […]

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Category Archives: Data Operations Columns