Techsplainers by IBM

IBM
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Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.

  1. What is data quality?

    5 小時前

    What is data quality?

    This episode of Techsplainers explores data quality—the measure of how well datasets meet criteria for accuracy, completeness, validity, consistency, uniqueness, timeliness, and fitness for purpose. We examine the seven key dimensions of data quality and explain how they impact business decisions, processes, and customer satisfaction. The discussion highlights the critical distinction between data quality, data integrity, and data profiling, while explaining why poor quality data costs organizations an average of USD 12.9 million annually (according to Gartner research). We also explore the growing importance of data quality for AI and machine learning systems, where the "garbage in, garbage out" principle directly affects outcomes. Whether you're in marketing, supply chain management, or healthcare, understanding data quality fundamentals is essential for making reliable, data-driven decisions.    Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Mimi Sun Longo

    7 分鐘
  2. What code LLMs mean for the future of software development

    3 天前

    What code LLMs mean for the future of software development

    This episode of Techsplainers explores Code LLMs, specialized AI models that are transforming software development by understanding, generating, and explaining code. We examine how these models differ from general-purpose LLMs through their extensive training on programming languages, documentation, and code repositories, giving them a deeper understanding of software development concepts and patterns. The discussion covers how Code LLMs work through transformer architecture and reinforcement learning from human feedback, as well as their substantial benefits for developers, including increased productivity, enhanced learning opportunities, improved documentation, and democratized access to coding. We highlight practical applications such as code generation, bug fixing, refactoring, and test creation, while also addressing important limitations including potential security vulnerabilities, challenges with complex code, intellectual property concerns, and the risk of over-reliance. The episode concludes with insights into how these tools are reshaping the development landscape, with developers increasingly shifting toward a supervisory role focused on architecture and design decisions. Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

    8 分鐘
  3. What is COBOL modernization?

    4 天前

    What is COBOL modernization?

    This episode of Techsplainers explores COBOL modernization strategies for organizations managing critical legacy systems written in this 60-year-old programming language. We examine why COBOL remains vital today—processing 95% of ATM transactions and 90% of global financial transactions—while highlighting the pressing challenges of maintaining these systems amid a growing skills gap, integration difficulties, and scalability concerns. The discussion covers various modernization approaches, from less disruptive strategies like rehosting and refactoring to more transformative methods like rearchitecting and replacement. We share key best practices for successful modernization, including thorough application documentation, business-value prioritization, preservation of essential business logic, and incremental implementation. The episode emphasizes that effective COBOL modernization isn't about wholesale replacement but thoughtful evolution that preserves decades of refined business logic while enabling future innovation. Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

    8 分鐘
  4. What is legacy code?

    5 天前

    What is legacy code?

    This episode of Techsplainers explores legacy code—software that continues to deliver value despite being inherited, outdated, or difficult to modify. We examine how these systems, though challenging, often represent significant business value and intellectual property, running critical operations across industries from banking to government. The discussion covers the main challenges legacy code presents: knowledge gaps from departed developers, accumulated technical debt, outdated technologies, poor documentation, and integration difficulties. We explore practical approaches to managing legacy systems, including incremental modernization through refactoring, the service wrapper approach, complete rewrites when necessary, and hybrid strategies. The episode concludes with best practices for working effectively with legacy code, emphasizing the importance of documentation, testing, incremental changes, and maintaining respect for systems that have successfully powered business operations for years. Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

    7 分鐘
  5. AI code documentation: Benefits and top tips

    6 天前

    AI code documentation: Benefits and top tips

    This episode of Techsplainers explores how artificial intelligence is transforming one of developers' most dreaded tasks: code documentation. We examine how AI-powered tools can automatically generate human-readable explanations of code, bringing consistency, efficiency, and improved maintenance to software development teams. The discussion covers key benefits of AI documentation, including time savings, comprehensive coverage, and knowledge preservation, while providing practical tips for effectively implementing these tools. We highlight the importance of using AI as a starting point rather than a complete solution, establishing clear documentation standards, and integrating tools directly into development workflows. The episode also addresses current limitations of AI documentation and the evolving landscape of tools that are making documentation more interactive and contextually relevant. Whether you're a seasoned developer or new to programming, this episode offers valuable insights into how AI is solving one of software development's persistent challenges.  Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

    7 分鐘
  6. What is code refactoring?

    2月23日

    What is code refactoring?

    This episode of Techsplainers explores Code LLMs, specialized AI models that are transforming software development by understanding, generating, and explaining code. We examine how these models differ from general-purpose LLMs through their extensive training on programming languages, documentation, and code repositories, giving them a deeper understanding of software development concepts and patterns. The discussion covers how Code LLMs work through transformer architecture and reinforcement learning from human feedback, as well as their substantial benefits for developers, including increased productivity, enhanced learning opportunities, improved documentation, and democratized access to coding. We highlight practical applications such as code generation, bug fixing, refactoring, and test creation, while also addressing important limitations including potential security vulnerabilities, challenges with complex code, intellectual property concerns, and the risk of over-reliance. The episode concludes with insights into how these tools are reshaping the development landscape, with developers increasingly shifting toward a supervisory role focused on architecture and design decisions. Find more information at https://www.ibm.biz/techsplainers-podcast Narrated by Erika Russi

    8 分鐘
  7. iPaaS examples and use cases

    2月20日

    iPaaS examples and use cases

    This episode of Techsplainers explores Integration Platform as a Service (iPaaS), a cloud-native solution that connects disparate business systems and applications. We examine how iPaaS differs from traditional middleware approaches and note key use cases including data synchronization, streamlined automations, AI-powered optimization, governance, and B2B integration.     The episode highlights industry-specific applications in healthcare, banking, and manufacturing, along with significant benefits like operational efficiency, improved accessibility through no-code tools, and enhanced security. We also discuss future trends, including how iPaaS helps combat SaaS sprawl and leverage unstructured data for AI training and autonomous agent development. With organizations achieving up to 345% ROI after implementation, iPaaS is becoming an essential component of modern digital transformation strategies.  Find more information at https://www.ibm.biz/techsplainers-podcast   Narrated by Dan Segal

    10 分鐘
  8. What is iPaaS (integration platform as a service)?

    2月19日

    What is iPaaS (integration platform as a service)?

    This episode of Techsplainers explores Integration Platform as a Service (iPaaS), a cloud-based solution that connects applications, systems, and data sources across diverse IT environments. We explain how iPaaS emerged to address the challenge of SaaS sprawl—where organizations use hundreds of different applications—and how it offers pre-built connectors, low-code interfaces, and centralized monitoring. The episode walks through how iPaaS works, how it compares to traditional approaches like Enterprise Service Buses and API management, and its various use cases from app-to-app integration to AI-powered workflows. Listeners will learn about the benefits of iPaaS, including reduced complexity, lower costs, improved data accessibility, and increased scalability, all of which help organizations streamline operations and break down data silos in increasingly complex IT ecosystems.  Find more information at https://www.ibm.biz/techsplainers-podcast   Narrated by Dan Segal

    7 分鐘
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簡介

Introducing the Techsplainers by IBM podcast, your new podcast for quick, powerful takes on today’s most important AI and tech topics. Each episode brings you bite-sized learning designed to fit your day, whether you’re driving, exercising, or just curious for something new. This is just the beginning. Tune in every weekday at 6 AM ET for fresh insights, new voices, and smarter learning.

資訊

  • 創作者
    IBM
  • 活躍年代
    2025年 - 2026年
  • 集數
    82
  • 年齡分級
    兒少適宜
  • 版權
    © IBM
  • 節目網站
    Techsplainers by IBM

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