CIO
JANUARY 17, 2023
Building and managing infrastructure yourself gives you more control — but the effort to keep it all under control can take resources away from innovation in other areas. They struggled to get new data insights developed into analyses,” he says. This saves a ton of mental load for data engineers and data analysts,” he says.
CIO
APRIL 23, 2025
Maintaining legacy systems can consume a substantial share of IT budgets up to 70% according to some analyses diverting resources that could otherwise be invested in innovation and digital transformation. data lake for exploration, data warehouse for BI, separate ML platforms).
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CIO
SEPTEMBER 12, 2022
Since joining NJ Transit, Fazal has primarily been chipping away at his major goal: enabling data innovation. Data engine on wheels’. To mine more data out of a dated infrastructure, Fazal first had to modernize NJ Transit’s stack from the ground up to be geared for business benefit. NJ Transit.
CIO
MARCH 13, 2025
The answer informs how you integrate innovation into your operations and balance competing priorities to drive long-term success. Companies like Qualcomm have to plan and commit well in advance, estimating chip production cycles while simultaneously innovating at breakneck speed. They dont just react to change; they engineer it.
Xebia
JANUARY 19, 2023
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.
CIO
MARCH 13, 2025
Weve been innovating with AI, ML, and LLMs for years, he says. Gen AI-related job listings were particularly common in roles such as data scientists and data engineers, and in software development. We currently have about 10 AI engineers and next year, itll be around 30. But not every company can say the same.
CIO
NOVEMBER 19, 2024
The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows. The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both.
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