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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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The 10 most in-demand tech jobs for 2023 — and how to hire for them

CIO

Database developers should have experience with NoSQL databases, Oracle Database, big data infrastructure, and big data engines such as Hadoop. Front-end developers write and analyze code, debug applications, and have a strong understanding of databases and networks.

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12 data science certifications that will pay off

CIO

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Check out our list of top big data and data analytics certifications.)

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Kubernetes for Big Data Workloads

Abhishek Tiwari

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.

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Unearthing the Value of Network Traffic Data with Big Data Network Analytics

Kentik

Seeing Beneath the Surface with Post-Hadoop Big Data. Irwin’s story may be interesting, but what does it have to do with network traffic data? The answer is rooted in the experience of Kentik’s founders, who’ve spent decades building and operating some of the world’s biggest and most complex networks.

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Building a Big Data Culture

Cloudera

In an earlier VISION post, The Five Markers on Your Big Data Journey , Amy O’Connor shared some common traits of many of the most successful data-driven companies. In this blog, I’d like to explore what I believe is the most important of those traits, building and fostering a culture of data. .

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Core technologies and tools for AI, big data, and cloud computing

O'Reilly Media - Ideas

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. Data Platforms. Data Integration and Data Pipelines. Model lifecycle management.