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Unapologetically Technical Episode 18 – Adrian Woodhead

Jesse Anderson

In this episode of Unapologetically Technical, I interview Adrian Woodhead, a distinguished software engineer at Human and a true trailblazer in the European Hadoop ecosystem. ” Dont forget to subscribe to my YouTube channel to get the latest on Unapologetically Technical!

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Data Integrity for AI: What’s Old is New Again

Precisely

But those end users werent always clear on which data they should use for which reports, as the data definitions were often unclear or conflicting. Then came Big Data and Hadoop! The big data boom was born, and Hadoop was its poster child. A data lake!

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How to get started with dbt

Christophe Blefari

dbt was born out of the analysis that more and more companies were switching from on-premise Hadoop data infrastructure to cloud data warehouses. You can read dbt's official definitions. In this resource hub I'll mainly focus on dbt Core— i.e. dbt. First let's understand why dbt exists.

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A Definitive Guide to Using BigQuery Efficiently

Towards Data Science

No matter if it is a CSV file, ORC / Parquet files from a Hadoop ecosystem or any other source. A Definitive Guide to Using BigQuery Efficiently was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story. GB / 1024 = 0.0056 TB * $8.13 = $0.05

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Hadoop The Definitive Guide; Best Book for Hadoop

ProjectPro

We usually refer to the information available on sites like ProjectPro, where the free resources are quite informative, when it comes to learning about Hadoop and its components. ” The Hadoop Definitive Guide by Tom White could be The Guide in fulfilling your dream to pursue a career as a Hadoop developer or a big data professional. .”

Hadoop 40
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How to learn data engineering

Christophe Blefari

Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. In order to understand today's data engineering I think that this is important to at least know Hadoop concepts and context and computer science basics.

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How to develop Spark applications with Zeppelin notebooks

Team Data Science

You can run it on a server and you can run it on your Hadoop cluster or whatever. I'm definitely convinced that you need this Zeppelin stuff. Especially working with dataframes and SparkSQL is a blast. What is a Zeppelin? A Zeppelin is a tool, a notebook tool, just like Jupiter. And it can run Spark jobs in the background.

Hadoop 130