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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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Healthcare organizations must create a strong data foundation to fully benefit from generative AI

CIO

That amount of data is more than twice the data currently housed in the U.S. Nearly 80% of hospital data is unstructured and most of it has been underutilized until now. To build effective and scalable generative AI solutions, healthcare organizations will have to think beyond the models that are visible at the surface.

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10 highest-paying IT jobs

CIO

There’s an ever-growing need for technical pros who can handle the rapid pace of technology, ensuring businesses keep up with industry standards, compliance regulations, and emerging or disruptive technologies. The demand for specialized skills has boosted salaries in cybersecurity, data, engineering, development, and program management.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning - AI

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. Consider your security posture, governance, and operational excellence when assessing overall readiness to develop generative AI with LLMs and your organizational resiliency to any potential impacts.

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Data Architect: Role Description, Skills, Certifications and When to Hire

Altexsoft

Data architect and other data science roles compared Data architect vs data engineer Data engineer is an IT specialist that develops, tests, and maintains data pipelines to bring together data from various sources and make it available for data scientists and other specialists.

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Navigating the Data Lake: Insights from Building and Utilizing Data Lakes

InnovationM

Technologies Behind Data Lake Construction Distributed Storage Systems: When building data lakes, distributed storage systems play a critical role. These systems ensure high availability and facilitate the storage of massive data volumes. Data Ingestion Tools: The journey of constructing a data lake starts with data ingestion.

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DevOps in a data science world

Xebia

Ideally, ‘ facilitate individual business domains with their ‘insights’ demand ’ means: individual business domains are capable to take ownership of creating and operating their own ‘data and insights’ needs. Let’s first briefly explore the world of Data Science and better understand why DevOps can help.

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