Would you use open lakehouse architecture? Can you explain why or why not in the comments?

Question

Answer

Agility and innovation of architecture have become more crucial than ever before. It's no longer sufficient for organizations to confine themselves to standard data warehouses solely for structured data. With the diverse range of decision intelligence encompassing ( BI, ML, AI and even GenAI) alongside the varied data types including structured, semi-structured, and unstructured data, adaptation to Data Lakehouse is imperative.

The expectation now is that any type and source of data should be readily available for consumption, boosting business agility and accommodating the growing variety of requirements and use case development.

Would you use open lakehouse architecture? Can you explain why or why not in the comments?

Content you might like

Curious which is more common: data mesh vs data fabric. Is your org employing one of these?

Thinking about your organization as a whole, what would you say are its top business objectives for the next two years?

If you had a magic wand - what's the #1 daily business challenge you'd eliminate?

What is the best advice that you've received around balanced data governance that allows access while protecting data?

Have you set up human-in-the-loop interfaces for your AI systems? How did you decide where to bring humans in?