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Six Data Quality Dimensions to Get Your Data AI-Ready
If you look at Google Trends, you’ll see that the explosion of searches for generative AI (GenAI) and large language models correlates with the introduction of ChatGPT back in November 2022. GenAI has brought hope and promise for those who have the creativity and innovation to dream big, and many have formulated impressive and pioneering […]


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Author: Allison Connelly

The End of Agile – Part 4 (Lessons from Agile)
In my first article, I laid out the basic premise for this series: an examination of how Agile has gone from the darling of the application development community to a virtual pariah that nobody wants to be associated with, and an exploration of the very important question of what we should replace it with. We […]


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Author: Larry Burns

Master Data Match Rules
As part of a master data management (MDM) implementation, a series of rules must be implemented to determine if two records refer to the same real-world entity that they represent. In the world of MDM, this is often referred to as the golden record, and master data match rules identify when two should become one.  Introduction  […]


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Author: Mark Horseman

New Gartner Category Impacts Data Governance Professionals
With the latest SEC developments lighting a fire under the feet of companies and their executives, data governance is increasingly a front-line imperative. The shift is dramatic, with firms now mandated to report material cybersecurity incidents promptly, a move that ties the knot even tighter between cybersecurity and data governance. As highlighted in the “Data […]


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Author: Myles Suer

The End of Agile – Part 3 (What Is Agile Really?)
In the first article, I laid out the basic premise for this series: an examination of how Agile has gone from the darling of the application development community to a virtual pariah that nobody wants to be associated with, and an exploration of the very important question of what we should replace it with. We […]


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Author: Larry Burns

Data Lifecycle Management: Optimizing Data Storage, Usage, and Disposal
The use of data worldwide for business and recreation has exploded in the last decade, with an estimated 328.77 million terabytes of data created every single day globally. In 2024, experts predict that nearly 120 zettabytes of new data will be created. All of this data creation has also created a substantial storage problem for […]


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Author: Ainsley Lawrence

Data Governance Made Simple
Those of us in the field of enterprise data management are familiar with the many authors contributing their knowledge and expertise to the data management body of knowledge.[1] We are also very familiar with the many, varied, and often conflicting ways in which data management terms are used. “Data architecture,” “data integration,” and even terms […]


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Author: William Burkett

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 […]


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Author: Melanie Mecca

Data Crime: Arizona Is Not Arkansas
I call it a “data crime” when someone is abusing or misusing data. When we understand these stories and their implications, it can help us learn from mistakes and prevent future data crimes. The stories can also be helpful if you have to explain the importance of data management to someone. The Story After a series […]


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Author: Merrill Albert

The End of Agile – Part 2 (Critiques of Agile)
In the first article, I laid out the basic premise for this series: an examination of how Agile has gone from the darling of the application development community to a virtual pariah that nobody wants to be associated with, and an exploration of the very important question of what we should replace it with. We […]


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Author: Larry Burns

Data Governance Gets a New Impetus
Data governance has often been met with furrowed brows among CIOs — sometimes seen as the broccoli of the IT dinner plate: undoubtedly good for you, but not always eagerly consumed. CIOs often bore the brunt from organizations that were forced to do top-down data governance. With this said, defensive data governance has been a […]


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Author: Myles Suer

The Importance of Data Due Diligence
Acquiring an existing business can be an exceptional way to make your entrepreneurial dreams come to life — or even diversify your investment portfolio. But, unless you do your research well, you’re opening yourself up to a lot of unnecessary risk. The process of due diligence involves the appraisal and assessment of a potential investment, […]


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Author: Sarah Kaminski

The End of Agile – Part 1 (A Brief History of Agile)
In recent years, we have seen substantial pushback on many fronts against Agile as a viable and important project management methodology. In my 2016 book, “Growing Business Intelligence”[i] (a book about Agile BI), I quoted from a 2014 article by Dave Thomas, one of the signers of the “Agile Manifesto,” in which he recommended retiring […]


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Author: Larry Burns

Creative Ways to Surf Your Data Using Virtual and Augmented Reality
Organizations often struggle with finding nuggets of information buried within their data to achieve their business goals. Technology sometimes comes along to offer some interesting solutions that can bridge that gap for teams that practice good data management hygiene. We’re going to take a look deep into the recesses of creativity and peek at two […]


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Author: Mark Horseman

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 […]


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Author: Daragh O Brien

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 […]


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Author: William A. Tanenbaum

Data Cleansing Tools for Big Data: Challenges and Solutions
In the realm of big data, ensuring the reliability and accuracy of data is crucial for making well-informed decisions and actionable insights. Data cleansing, the process of detecting and correcting errors and inconsistencies in datasets, is critical to maintaining data quality. However, the scale and complexity of big data present unique challenges for data cleansing […]


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Author: Irfan Gowani

Getting the BELT: Empowering Executive Leadership in Data Governance
The expression “Getting the Belt” has several meanings. This phrase most commonly refers to a form of corporal punishment where a belt is used by an authority figure to spank or hit someone as a punitive measure. This form of discipline is now, thankfully, regarded as inappropriate and harmful. Additional meanings signify winning a championship […]


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Author: Robert S. Seiner

Explaining the Why Behind Data Quality Dimensions
Data quality is measured across dimensions, but why? Data quality metrics exist to support the business. The value of a data quality program resides in the ability to take action to improve data to make it more correct and therefore more valuable. The shorter the amount of time between the discovery of the data quality […]


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Author: Allison Connelly

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 […]


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Author: Dave McComb

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 […]


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Author: Randall Gordon

5 Best Practices for Data Management in the Cloud
Organizations manage data in the cloud through strategic planning and the implementation of best practices tailored to their specific needs. This involves selecting the right cloud service providers and technology stacks that align with their data management goals. They focus on data security, compliance, and scalability while leveraging cloud technologies to enhance data accessibility, analysis, […]


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Author: Gilad David Maayan

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 […]


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Author: Steve Zagoudis