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What is a data engineer? An analytics role in high demand

CIO

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. The data engineer role.

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Sigmoid raises $12 million to scale its data engineering and analytics platform

TechCrunch

As long-term partners, we are excited to double down on their goal to be the premier engineered data solutions and AI provider for accelerating digital transformation for enterprises across industries,” said Anandamoy Roychowdhary, principal, Sequoia Southeast Asia, in a prepared statement.

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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.

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From legacy to lakehouse: Centralizing insurance data with Delta Lake

CIO

I believe that the fundamental design principles behind these systems, being siloed, batch-focused, schema-rigid and often proprietary, are inherently misaligned with the demands of our modern, agile, data-centric and AI-enabled insurance industry. data lake for exploration, data warehouse for BI, separate ML platforms).

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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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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. Were building a department of AI engineering, mostly by bringing in people from data engineering and training them to work with gen AI and AI in general, says Daniel Avancini, Indiciums CDO.

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AI data readiness: C-suite fantasy, big IT problem

CIO

The legacy problem Legacy systems that collect and store limited data are part of the problem, says Rupert Brown, CTO and founder of Evidology Systems, a compliance solutions provider. Data quality is a problem that is going to limit the usefulness of AI technologies for the foreseeable future, Brown adds.

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