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The future of data: A 5-pillar approach to modern data management

CIO

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. Operational errors because of manual management of data platforms can be extremely costly in the long run.

Data 167
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How FiveStars re-engineered its data engineering stack

CIO

It shows in his reluctance to run his own servers but it’s perhaps most obvious in his attitude to data engineering, where he’s nearing the end of a five-year journey to automate or outsource much of the mundane maintenance work and focus internal resources on data analysis. It’s not a good use of our time either.”

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IT leaders: What’s the gameplan as tech badly outpaces talent?

CIO

Gen AI-related job listings were particularly common in roles such as data scientists and data engineers, and in software development. Their pay scales often dont afford top technical talent and often dont have technical leadership that can accurately and adequately vet the people theyre interviewing, he says.

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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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From legacy to lakehouse: Centralizing insurance data with Delta Lake

CIO

It addresses fundamental challenges in data quality, versioning and integration, facilitating the development and deployment of high-performance GenAI models. data lake for exploration, data warehouse for BI, separate ML platforms).

Insurance 164
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IDC chief research officer: GenAI, from experimentation to adoption

CIO

Organizations are finding they have outdated data or incomplete data sets. Companies tend to invest heavily in the data plane where data is stored, organized and managed. Now, they need to invest in data engineering to prepare data for grounding and fine-tuning their AI models.

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United Airlines’ AI strategy: The airline that makes decisions fastest wins

CIO

Much of this work has been in organizing our data and building a secure platform for machine learning and other AI modeling. We also built an organization skilled in the data engineering and data science required for AI. Well continue to need data engineering and analytics, data science, and prompt engineering.

Airlines 124