April 25, 2025
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data quality

Data Crime: Arizona Is Not Arkansas

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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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How Data Analytics Is Transforming Due Diligence

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Due diligence is the complex process of assessing a potential investment and ensuring it is a sound one. It involves the gathering, classifying, and analyzing of large volumes of data. Given its very nature, it’s the perfect field for data analytics, which can speed processes up and assess the quality and reliability of data. Due…

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How to Become a Citizen Data Scientist

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The job responsibilities of a citizen data scientist include dealing with new data, using automated tools to process big data, and creating additional models to gain additional insights. Their primary job is not to make predictions directly from big data, or develop prescriptive analytics, but to build models and use tools that accomplish those goals….

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Metadata Governance: An Outline for Success (Part Two)

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In part one of “Metadata Governance: An Outline for Success,” I discussed the steps required to implement a successful data governance environment, what data to gather to populate the environment, and how to gather the data. In part two, I will discuss the “so what” aspects of data governance — that is, what types of…

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

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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…

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Managing Missing Data in Analytics

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Today, corporate boards and executives understand the importance of data and analytics for improved business performance. However, most of the data in enterprises is of poor quality, hence the majority of the data and analytics fail. To improve the quality of data, more than 80% of the work in data analytics projects is on data…

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Data Professional Introspective: Accelerating Enterprise Data Quality

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My recent columns have focused on actionable initiatives that can both deliver business value, providing a tangible achievement, and raise the profile of the data management organization data management organization (DMO).(For more on the DMO, a plug-and-play initial organization was proposed in an earlier TDAN column, “Coming in from the Cold.”) In that light, let’s…

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9 Best Practices for Real-Time Data Management

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In the era of digital transformation, data has become the new oil. Businesses increasingly rely on real-time data to make informed decisions, improve customer experiences, and gain a competitive edge. However, managing and handling real-time data can be challenging due to its volume, velocity, and variety. This article will guide you through nine best practices…

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