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Bridging the Skills Gap: Simplify Data Engineering in Fabric


The shift to modern data architectures like Spark-based lakehouses in Microsoft Fabric is transforming the data landscape. However, for many BI professionals trained in SQL, this transition introduces steep learning curves with tools like PySpark, Delta Lake, and Jupyter notebooks. Meanwhile, the rise of AI-generated code presents additional challenges, including low accuracy, poor maintainability, and increased reliance on senior engineers.


What you'll learn

In this webinar, we’ll explore how TimeXtender’s metadata-driven approach empowers BI professionals to thrive in Microsoft Fabric without requiring deep Spark expertise.
  • How TimeXtender bridges the skills gap by enabling SQL-trained teams to design enterprise-grade solutions visually while generating optimized Spark code behind the scenes.
  • Practical ways TimeXtender automates complex tasks like dependency management, resource scaling, and Delta table optimization, allowing BI professionals to focus on delivering insights rather than troubleshooting code.
  • Strategies to overcome the challenges of AI-generated code, including ensuring consistency, maintainability, and scalability across your data solutions.
Whether you’re a BI professional looking to upskill or a leader seeking to empower your team in Microsoft Fabric, this session will provide actionable insights and tools to accelerate your journey while maintaining enterprise-grade standards.

Your Presenter

Joseph Treadwell
Solutions Specialist
TimeXtender
  • Joseph Treadwell
    Solutions Specialist
    TimeXtender