Remove 2015 Remove Big Data Remove Data Engineering Remove Scalability
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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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Immuta raises $1.5M to manage the chaos of big data systems

CTOvision

RESTON, VA – July 09, 2015: Sequoia Apps, the new venture investment arm of Sequoia Holdings, Inc announced today that it has closed its first series seed investment in Immuta, Inc. Immuta, a next-gen enterprise data management platform provider, recently closed a heavily oversubscribed seed round, led by Blu Venture Investors, LLC.

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The IBM Press Release on Spark That Every Tech Leader Should Read

CTOvision

They also launched a plan to train over a million data scientists and data engineers on Spark. BM Joins Spark Community, Plans to Educate More Than 1 Million Data Scientists. The endorsement came in the form of a $300 million investment and the assignment of 3,500 people to help develop Spark.

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Big Data in Healthcare: Sources and Real-World Applications

Altexsoft

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

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AI Chihuahua! Part I: Why Machine Learning is Dogged by Failure and Delays

d2iq

2015): Hidden Technical Debt in Machine Learning Systems. Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. The data engineer’s main focus is on ETL: extracting, transforming, and loading data.

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Azure vs AWS: How to Choose the Cloud Service Provider?

Existek

And companies that have completed it emphasize gained advantages like accessibility, scalability, cost-effectiveness, etc. . Along with meeting customer needs for computing and storage, they continued extending services by presenting products dealing with analytics, Big Data, and IoT. Read the article.

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The Good and the Bad of Apache Airflow Pipeline Orchestration

Altexsoft

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. What is Apache Airflow?