Secrets of Data Analytics Leaders Eckerson Group

Explore the reasons for data engineers to collaborate with data scientists, machine learning (ML) engineers, and developers on DataOps initiatives that support GenAI.
Published at:
https://www.eckerson.com/articles/dataops-for-generative-ai-data-pipelines-part-iii-team-collaboration

This blog explores three criteria to evaluate tools that manage unstructured data pipelines for GenAI.
Published at:
https://www.eckerson.com/articles/data-engineering-for-genai-three-criteria-to-evaluate-pipeline-tools

If your data team wants to implement data products, it would be wise to avoid these 12 pitfalls that can torpedo an initiative.
Published at:
https://www.eckerson.com/articles/12-pitfalls-to-avoid-when-implementing-data-products

This article compares data catalogs and data marketplaces and argues that you need both and will soon have both as vendors add data marketplace extensions.
Published at:
https://www.eckerson.com/articles/why-do-i-need-a-data-marketplace-when-i-have-a-data-catalog

This blog defines conversational BI, why companies should consider it, and how their power and casual users can best get the desired results.
Published at:
https://www.eckerson.com/articles/driving-results-with-conversational-bi-best-practices-for-power-and-casual-users

Data engineering is now considered a crucial job in IT as Generative AI, the hottest technology of this decade, relies on data engineers to provide accurate inputs.
Published at:
https://www.eckerson.com/articles/data-engineering-for-genai-how-to-optimize-data-pipelines-and-governance