Posts Tagged ‘Data quality’
It’s Probably Your Data
When an artificial intelligence (AI) initiative underperforms, the model is often the first thing blamed. Maybe the algorithm isn’t sophisticated enough. Maybe the platform is wrong. Maybe the organization needs a newer, more powerful model. This interesting and important topic came to us from CIO in their article, “Your AI model isn’t the problem. Your…
Read MoreWhy AI Makes a Data Strategy More Important Than Ever
Artificial intelligence (AI) may be changing what organizations can do with data, but it hasn’t changed one fundamental truth: AI is only as effective as the data behind it. That makes a strong data strategy more important than ever. This interesting topic came to us from Dataversity in their article, “Your Data Strategy Isn’t Ready…
Read MoreData Quality Is Still the Foundation of Information Science
For information science professionals in higher education, data quality is hardly a new concern. Long before generative artificial intelligence (GenAI), machine learning and advanced analytics entered the conversation, the principle was simple: information systems can only be as trustworthy as the data they contain. This important topic came to us from IT Brief and their…
Read MoreGarbage In, Garbage Out: Why Are We Still Having This Conversation?
Artificial intelligence (AI) may be advancing at breakneck speed, but one stubborn truth hasn’t changed: AI is only as good as the data behind it. RT Insights brought this topic to us in their article, “Why AI Systems Are Only as Good as the Data Being Fed into Them“. This is not new news. “Garbage…
Read MoreFrom Information to Action: Turning Data into Better Decisions
Organizations today have access to more data than ever before. Customer behavior, operational performance, financial trends, market activity and employee insights can all be measured and analyzed. But having data and making good decisions with it are two very different things. This interesting topic came to us from IDB in their article, “How Can Governments…
Read MorePredictive Analytics in the Age of AI: Smarter Predictions, New Risks
Predictive analytics has always been about using what we know to make an educated guess about what comes next. By analyzing historical data, patterns and trends, organizations can forecast customer behavior, anticipate market shifts, identify risks and make better-informed decisions. This subject came to us from International Business Magazine in their article, “Predictive AI Analytics:…
Read MoreBeyond Adoption: What AI Maturity Really Means
Implementing artificial intelligence (AI) and being mature in your use of AI are two very different things. This interesting topic came to us from Concentrix in their blog post “The Analytics Catalyst – A Practical Framework for Data & AI Maturity.” AI maturity describes how effectively an organization moves from experimenting with AI to integrating…
Read MoreAI Isn’t the Data Problem. It’s the Spotlight.
Artificial intelligence (AI) may be dominating technology conversations, but underneath the excitement, urgency and evolving tools lies a very familiar challenge: data. AI did not create the data problem. It simply made it much harder to ignore. For years, organizations have struggled with fragmented information, inconsistent terminology, disconnected systems, weak metadata and poor governance. Those…
Read MoreWelcome to the Data Quality Conversation. We’ve Been Expecting You.
There is exciting news in the world of artificial intelligence (AI). Some of the largest corporations on the planet have recently discovered that AI needs good data to work properly. CU Today brought this subject to us in their article, “Bank Of America CEO Says AI’s Biggest Challenge Isn’t Technology—It’s Data Quality.“ We’ll give everyone…
Read MoreData Qualityis the Foundation of Successful AI Adoption
Artificial intelligence (AI) has enormous potential to transform organizations, but its success depends on one very critical factor: data quality. AI systems learn patterns, identify relationships and generate insights based entirely on the information they receive. If that information is inaccurate, incomplete or outdated, the results will be flawed. This important and timely topic came…
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