Automating Datalake Pipelines for AI

Automating Datalake Pipelines for AI

 

Siete ejemplos de uso de la integración y calidad de datos

Data engineers are facing increasing demands to deliver accurate, model-ready data to AI initiatives — fast. But traditional data integration tools require time-consuming coding by highly skilled staff. And these tools often lack the capabilities to fully prepare, cleanse, tag, and catalog the data.

What’s the answer? Automated data pipelines driven by AI and ML. In this eBook, you’ll learn how to build AI- and ML-enabled data pipelines for delivering AI-ready data.

Topics include:

  • Key considerations when you’re building data lakes for AI
  • 5 ways automation works across the data pipeline
  • A detailed checklist for success

You’ll also learn how Qlik can help, with a series of integrated solutions for automating your entire data lake pipeline — from real-time ingestion to processing and refinement — without requiring writing code.

White Paper from  Qlik_Logo

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