When Bad Data Starts Costing Real Money
Most organizations love to talk about being data driven. Fewer organizations want to talk about the spreadsheets held together with hope, duplicated records nobody trusts and mystery field labels. Yet that messy reality is exactly why data quality platforms have become less of a luxury and more of a survival tool. Tech Target brought this…
Read MoreBuilding a Data Culture People Will Actually Use
Let’s be honest. Most people do not wake up excited about data governance. No one is lighting candles around a beautifully organized spreadsheet whispering, “Ah yes, metadata.” But organizations that treat data seriously almost always function better, move faster and make smarter decisions. This important topic came to us from CIO in their article, “What…
Read MoreFrom Algorithms to Hallucinations: How AI Created a New Business Vocabulary
Artificial intelligence (AI) has not only transformed technology and business operations, it has also introduced an entirely new language into the workplace. Terms that once lived primarily in research labs or science fiction are now appearing in board meetings, marketing plans, compliance discussions and coffee-break conversations. Suddenly, everyone is talking about prompts, embeddings, vectors and…
Read MoreData and AI Governance: Why They Must Work Together
Artificial intelligence (AI) may be the shiny new engine driving innovation, but data remains the fuel. And like any high-powered machine, the quality of the fuel matters. Organizations rushing to adopt AI are quickly discovering that AI governance and data governance are not separate conversations. They are deeply interconnected disciplines that must work together to…
Read MoreGenerative AI: Exciting, Impressive and Occasionally a Little Chaotic
Generative AI (GenAI) has quickly become one of the most talked-about technologies in business, and honestly, it is easy to see why. It can write content, summarize information, help develop software, automate repetitive tasks and uncover insights in seconds that might have taken humans hours or days. Whether you love it, fear it or are…
Read MoreMapping the Lifeblood of Business
Data moves through modern businesses like electricity through a city grid. It powers customer service, finance, analytics and now increasingly, artificial intelligence (AI). But many organizations still do not fully understand where their data originates, where it travels, who touches it or how it changes along the way. In the age of AI, that lack…
Read MoreWhen Technology Gets a Little… Personal
There was a time when innovation meant faster computers, smaller phones and maybe a refrigerator that might judge you for buying off-brand yogurt. But now? Technology has entered its bold era. This interesting and somewhat humorous information came to us from Futurist Speaker in their article, “Twelve Inventions That Prove the Future Has a Sense…
Read MoreDecentralizing Data for a Smarter, More Secure Network
The Internet of Things (IoT) has rapidly expanded, connecting everything from smart thermostats to industrial sensors. But as the number of devices grows, so does the complexity of managing the data they generate. Traditionally, IoT systems rely on centralized platforms to collect, process and store this data. While effective, this model introduces challenges around scalability,…
Read MoreOntology: The Invisible Architecture Powering Findability in the Age of AI
In information science, ontology is one of those terms that sounds intimidating but quietly does some of the most important work behind the scenes. At its core, an ontology is a structured framework that defines the relationships between concepts within a domain. It goes beyond simple lists of terms or categories by mapping how ideas…
Read MoreRecords Retention in the Age of AI: Why Taxonomy Still Reigns Supreme
In a world increasingly shaped by artificial intelligence (AI), records retention has moved from back-office obligation to strategic necessity. AI systems thrive on data, but not just any data—relevant, accurate, well-structured data. Without intentional retention policies, organizations risk feeding their AI outdated, redundant or even harmful information, leading to flawed outputs and questionable decisions. This…
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