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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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Remember when developers reigned supreme? The market for software coding goes soft

CIO

It seems like only yesterday when software developers were on top of the world, and anyone with basic coding experience could get multiple job offers. This yesterday, however, was five to six years ago, and developers are no longer the kings and queens of the IT employment hill.

Marketing 152
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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. We currently have about 10 AI engineers and next year, itll be around 30. Data engineering and data science are also difficult to hire for, but gen AI is even worse, he says.

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Beyond the hype: 4 use cases that show what’s actually working with gen AI

CIO

According to experts and other survey findings, in addition to sales and marketing, other top use cases include productivity, software development, and customer service. Use case 2: software development PGIM also uses gen AI for code generation, specifically using Github Copilot.

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The early returns on gen AI for software development

CIO

Generative AI is already having an impact on multiple areas of IT, most notably in software development. Still, gen AI for software development is in the nascent stages, so technology leaders and software teams can expect to encounter bumps in the road. “It One example is with document search and summarization.

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Why generic marketing approaches don’t work on software developers

TechCrunch

The educational and inspirational content you use to attract developers will depend on who is the best fit for your product. If you provide a mobile SDK, the right developer is building iOS and Android apps. If your customers are data engineers, it probably won’t make sense to discuss front-end web technologies.

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What is Data Engineering: Explaining Data Pipeline, Data Warehouse, and Data Engineer Role

Altexsoft

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.