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Many data engineers already use large language models to assist data ingestion, transformation, DataOps, and orchestration. This blog commences a series that explores the emergence of ChatGPT, Bard, and LLM tools from data pipeline vendors, and their implications for the discipline of data engineering.
Published at: https://www.eckerson.com/articles/should-ai-bots-build-your-data-pipelines-examining-the-role-of-chatgpt-and-large-language-models-in-data-engineering

Examining the Role of ChatGPT & Large Language Models in Data Engineering - Audio Blog

The unbundling of the data ecosystem is causing organizations to “duct tape” products and frameworks together to build their solutions and data delivery processes. Organizations fail to build and deploy end-to-end, automated, repeatable data-driven systems, ignoring data engineering & dataops principles as well as best practices.
Published at: https://www.eckerson.com/articles/dataops-in-data-engineering

DataOps In Data Engineering - Audio Blog

We talk about DataOps, but if you’re expecting this to be DevOps for data - you are mistaken. Today we talk about engineering data through the idea of data stewardship or how you manage and control the data. 

Beyond permissions and access into the costs and how things are stewarded, how logs are handled, who controls how much access and how quickly people have access, where you're putting the data to improve its effectiveness, and more. There is so much going on above the infrastructure, but below that actual analytics, this conversation will open your mind to a whole layer of challenges related to governing and managing data. 

Transcript: https://otter.ai/u/SDaRomv41JtQYM7a6C1Hy7cOpy8?utm_source=copy_url
Photo by Taryn Elliott: https://www.pexels.com/photo/person-holding-cupcake-with-white-icing-on-top-4099125/

Data + Operations = DataOps

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Let's reflect on the events of the past year and prognosticate on what may transpire in the months ahead.
Published at:
https://www.eckerson.com/articles/trends-for-2024-our-team-gazes-into-the-crystal-ball

Trends for 2024: Our Team Gazes into the Crystal Ball - Audio Blog

Data management practices have changed substantially since the early 1990s and the dawn of data warehousing.
Published at:
https://www.eckerson.com/articles/the-continuing-evolution-of-data-management

The Continuing Evolution Of Data Management - Audio Blog

The success of Generative AI depends on fundamental disciplines like DataOps.
Published at:
https://www.eckerson.com/articles/dataops-for-generative-ai-data-pipelines-part-i-what-and-why

DataOps for Generative AI Data Pipelines, Part I: What and Why - Audio blog

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

DataOps for Generative AI Data Pipelines, Part II: Must-Have Characteristics - Audio Blog

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

DataOps for Generative AI Data Pipelines, Part III: Team Collaboration - Audio Blog

Listen to data and analytics leaders share the secrets of their success. Wayne Eckerson, long-time global thought leader interviews guests who run data and analytics programs at Fortune 2000 organizations around the world. Tune in to stay abreast of the latest technologies, techniques, and trends in our fast-paced industry.

An excellent source for industry thought leadership in Edge Computing, Cloud Computing, DevOps, Open Source base on discussions at.the2030.cloud

New tracks tagged #dataops