Techsplainers by IBM

• What is observability?

  This episode of Techsplainers takes a deep dive into observability, a cornerstone of modern DevOps and cloud-native environments. We break down what observability really means—going beyond traditional monitoring to provide full-stack visibility into complex systems. You’ll learn about its three pillars: logs, traces, and metrics, and how they work together to deliver actionable insights. The discussion explores how observability empowers teams to troubleshoot faster, optimize performance, and improve user experience. We also examine cutting-edge innovations like AI-driven observability, predictive analytics, and causal AI, which are transforming how organizations prevent issues before they occur. Real-world benefits, common use cases, and the role of observability in accelerating DevOps pipelines round out this comprehensive guide to one of today’s most critical tech practices.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by PJ Hagerty

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• What is data quality management?

  This episode of Techsplainers explains data quality management (DQM)—a set of practices that ensure data is accurate, complete, consistent, timely, unique, and valid. Learn why high-quality data is critical for business intelligence, regulatory compliance, and AI performance, and explore key techniques like data profiling, cleansing, validation, and monitoring.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by Matt Finio

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• What is a data fabric?

  This episode of Techsplainers explains what a data fabric is and why it’s critical for modern enterprises. A data fabric is a data architecture that unifies and democratizes data access across hybrid and multicloud environments. It uses AI, metadata, and automation to break down silos, improve governance, and enable self-service data access—accelerating analytics, decision-making, and AI adoption.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by Matt Finio

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• What is a data lakehouse?

  This episode of Techsplainers explains what a data lakehouse is and why it’s transforming modern data management. A data lakehouse combines the low-cost, flexible storage of data lakes with the high-performance analytics of data warehouses, enabling unified data systems for advanced analytics and AI. Learn how lakehouses evolved, their architecture, and how they compare to data lakes and warehouses.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by Matt Finio

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• What is a data lake?

  This episode of Techsplainers explains what a data lake is, how it evolved, and why it’s a cornerstone of modern data architecture. We cover its role in storing massive amounts of raw data in any format, its cloud-based foundations, and how it supports AI and machine learning workloads. Plus, learn how data lakes compare to warehouses and lakehouses.Find more information at https://www.ibm.com/think/podcasts/techsplainersNarrated by Matt Finio

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