Category: On-Demand Webinar

Accelerate AI Innovation: Build the Right Real-Time Data Architecture

Posted on by Striim Team | 1 min read | 3 views

Real-time data has become a non-negotiable foundation for powering machine learning (ML) and generative AI (GenAI). From delivering event-driven predictions to powering live recommendations and dynamic chatbot conversations, AI/ML initiatives depend on the continuous movement, transformation, and synchronization of diverse datasets across clouds, applications, and databases.

But complexity stands in the way: incompatible platforms, brittle pipelines, fragmented architectures, and the growing pressure of data privacy and compliance risks make it challenging for teams to deliver trusted, real-time data to models and applications.

In this webinar with BARC, a leading analyst firm for data & analytics and enterprise software, you’ll learn how to overcome these challenges and build the data backbone for AI/ML success.

Join us to:

Break down the key elements of modern data streaming architectures and their impact on AI/ML.
Define the must-have characteristics of a data streaming architecture.
Explore real-world use cases, including streaming ELT for experimentation, real-time ML, and retrieval-augmented generation (RAG) for GenAI.
Gain actionable guidance to build scalable, resilient streaming pipelines that drive continuous innovation and measurable value.

Executives and practitioners leading data and AI transformation — learn what it takes to stay competitive. Register today!

Scaling Strategic Governance of AI-Driven Data Across Your Organization

Posted on by Striim Team | 1 min read | 3 views

Join us to explore how addressing ethical considerations like bias and fairness can enhance your company’s reputation, while robust privacy measures help ensure regulatory compliance. Our expert panel will discuss strategies to improve transparency in AI processes, enabling informed decision-making, and how collaboration across industries can strengthen governance frameworks.

Key takeaways:

  • Ethical AI: How to mitigate bias and fairness issues to improve brand perception and public trust.
  • Privacy & Compliance: How to implement privacy measures that align with regulations and reduce legal risks.
  • Transparency: How clear communication about AI systems enhances decision-making and business agility.
  • Security: How to safeguard sensitive information to build customer trust and ensure business continuity.
  • Adaptability: How flexible governance frameworks enable businesses to stay ahead of emerging technologies.

Don’t miss this opportunity to discover how business leaders, data professionals, and strategists can build a comprehensive governance framework for AI-driven data and elevate their data strategy to drive business success.

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