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Oct 1 2025
Stop Feeding AI Junk: A Systematic Approach to Unstructured Data Ingestion
It’s go-time for enterprise AI. A PagerDuty global survey of 1,000 IT and business executives found that 62% of companies using agentic AI expect a return of 171% on average. But getting to ROI is no easy task. Recent surveys show mixed results on efforts thus far, with “getting strategies right” and “making data ‘AI-ready’” […]


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Author: Kumar Goswami

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Oct 1 2025
The Good AI: Data Contracts for AI Transparency
“AI is only as trustworthy as the data that fuels it.”  This statement has never been more relevant. AI systems now power decisions, affecting credit approvals, medical diagnoses, fraud detection, and countless other critical areas. Yet without transparency into data sources, quality, and lineage, AI can quickly become a black box — opaque, unpredictable, and […]


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Author: Subasini Periyakaruppan

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Sep 17 2025
Building a Data-First Culture
Technology is not what powers a data-first culture, but people, operating models, and disciplined delivery. Most organizations already possess more tools and data than they can effectively utilize. What differentiates the leaders is that they tie analytics to real business results, productize effective data, govern for speed and security, and, most importantly, rewire decisions. While […]


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Author: Chirag Agrawal

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Aug 6 2025
Data Speaks for Itself: Is Your Data Quality Management Practice Ready for AI?
While everyone is asking if their data is ready for AI, I want to ask a somewhat different question: Is your data quality management (DQM) program ready for AI?  In my opinion, you need to be able to answer yes to the following four questions before you can have any assurance you are ready to […]


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Author: Dr. John Talburt

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Jun 4 2025
Is the Scope of Data Governance Enough?
Data governance has long been the backbone of responsible data management, ensuring that organizations maintain high standards in data quality, security, and compliance. According to Jonathan Reichental in “Data Governance for Dummies,” the scope of governance extends well beyond data ownership and stewardship. It encompasses metadata, data architecture, master and reference data management, storage, integration, […]


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Author: Myles Suer

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Feb 19 2025
The Art of Lean Governance: Moving Beyond Governance Buzzwords and Bling
This column will expand on a Systems Thinking approach to Data Governance and focus on process control. The vendors of myriad governance tools focus on metadata, dictionaries, and quality metrics. Their marketing is a sea of buzzwords and bling — bells and whistles. Yet, where is the evidence of adding actual business value, defined as […]


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Author: Steve Zagoudis

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Feb 5 2025
Data Speaks for Itself: Data Quality Management in the Age of Language Models
Unsurprisingly, my last two columns discussed artificial intelligence (AI), specifically the impact of language models (LMs) on data curation. My August 2024 column, “The Shift from Syntactic to Semantic Data Curation and What It Means for Data Quality,” and my November 2024 column, “Data Validation, the Data Accuracy Imposter or Assistant?” addressed some of the […]


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Author: Dr. John Talburt

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Jan 15 2025
Identifying and Addressing Data Overload
Increased data generation requires modern businesses to manage vast volumes of information. All this data holds immense potential for insights and informed decision-making, but its value depends on effective utilization. Without the right tools, frameworks, and strategies, even established companies risk being overwhelmed by data overload.  Let’s take a closer look at data overload and […]


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Author: Irfan Gowani

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Dec 18 2024
The Challenges of Data Migration: Ensuring Smooth Transitions Between Systems
Data migration — the process of transferring data from one system to another — is a critical undertaking for organizations striving to upgrade infrastructure, consolidate systems, or adopt new technologies.   However, data migration challenges can be very complex, especially when doing large-scale data migration projects.   Duplicate or missing data, system compatibility issues, data security problems, […]


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Author: Ainsley Lawrence

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Dec 4 2024
Through the Looking Glass: What Does Data Quality Mean for Unstructured Data?
I go to data conferences. Frequently. Almost always right here in NYC. We have lots of data conferences here. Over the years, I’ve seen a trend — more and more emphasis on AI.   I’ve taken to asking a question at these conferences: What does data quality mean for unstructured data? This is my version of […]


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Author: Randall Gordon

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Dec 4 2024
Data Insights Ensure Quality Data and Confident Decisions
Every business (large or small) creates and depends upon data. One hundred years ago, businesses looked to leaders and experts to strategize and to create operational goals. Decisions were based on opinion, guesswork, and a complicated mixture of notes and records reflecting historical results that may or may not be relevant to the future.  Today, […]


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Author: Kartik Patel

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Nov 20 2024
Data Speaks for Itself: Data Validation – Data Accuracy Imposter or Assistant?
In my last article, “The Shift from Syntactic to Semantic Data Curation and What It Means for Data Quality” published in the August 2024 issue of this newsletter, I argued how the adoption of generative AI will change the focus and scope of data quality management (DQM). Because data quality is measured in the degree […]


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Author: Dr. John Talburt

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Nov 20 2024
The Art of Lean Governance: A Systems Thinking Approach to Data Governance
A systems thinking approach to process control and optimization demands continual data quality feedback loops. Moving the quality checks upstream to the source system provides the most extensive control coverage. Data quality approaches not utilizing these loops will fail to achieve the desired results, often worsening the problem.  Data Governance is about gaining trust and […]


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Author: Steve Zagoudis

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Nov 20 2024
Data Errors in Financial Services: Addressing the Real Cost of Poor Data Quality
Data quality issues continue to plague financial services organizations, resulting in costly fines, operational inefficiencies, and damage to reputations. Even industry leaders like Charles Schwab and Citibank have been severely impacted by poor data management, revealing the urgent need for more effective data quality processes across the sector.  Key Examples of Data Quality Failures  — […]


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Author: Angsuman Dutta

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Sep 18 2024
Data Quality: The Hidden Cornerstone of Digital Transformation Success
As organizations rush headlong into digital transformation initiatives, a critical factor often gets overlooked: data quality. In the race to implement cutting-edge technologies and overhaul business processes, many companies fail to recognize that the success of these efforts hinges on the accuracy, completeness, and reliability of their underlying data. This oversight can lead to disastrous […]


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Author: Christine Haskell

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Sep 18 2024
Data Crime: Your Phone Isn’t Here
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 the mistakes and prevent future data crimes. The stories can also be helpful if you must explain the importance of data management to someone.  The Story Last year, a […]


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Author: Merrill Albert

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Jun 19 2024
Data Crime: Bob Smith
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  I met Bob Smith! While that […]


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Author: Merrill Albert

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May 1 2024
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

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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 […]


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Author: Dr. John Talburt

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Apr 17 2024
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

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Apr 3 2024
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

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Mar 20 2024
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

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Mar 6 2024
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

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Feb 21 2024
Documenting Critical Data Elements
Many Data Governance or Data Quality programs focus on “critical data elements,” but what are they and what are some key features to document for them? A critical data element is any data element in your organization that has a high impact on your organization’s ability to execute its business strategy. An example is Customer Email […]


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Author: Mark Horseman

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Feb 7 2024
Stop Complaining About Your Data – And Do Something About It
Organizations are drowning in a sea of data, facing challenges that range from inconsistent quality to inefficient and ineffective management. It’s easy to complain about the state of your data, but a more productive tactic involves taking actionable steps to address these issues. Enter Non-Invasive Data Governance (NIDG) — a methodology that empowers organizations to […]


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Author: Robert S. Seiner

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