Secrets of Data Analytics Leaders Eckerson Group

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

Data engineers and data scientists must manage pipelines for unstructured data to ensure healthy inputs for language models.
Published at:
https://www.eckerson.com/articles/why-and-how-data-engineers-will-enable-the-next-phase-of-generative-ai

Companies that adopt DataOps increase the odds of success by making GenAI data pipelines what they should be: modular, scalable, robust, flexible, and governed.
Published: https://www.eckerson.com/articles/dataops-for-generative-ai-data-pipelines-part-ii-must-have-characteristics