Confessions of a Data Guy

DECEMBER 24, 2023

It’s true, even if you don’t want it to be. SparkSQL is destroying your data pipelines and possibly wreaking havoc on your entire data team, infrastructure, and life. In your heart of hearts, you’ve probably known it for years. With great power comes great responsibility. We all know that even us Data Engineers are human […] The post SparkSQL is Destroying your Pipelines appeared first on Confessions of a Data Guy.

Data Pipeline 147

Data Pipeline Data Engineering Data Engineer Engineering 147

Data Engineering Podcast

DECEMBER 24, 2023

Summary Kafka has become a ubiquitous technology, offering a simple method for coordinating events and data across different systems. Operating it at scale, however, is notoriously challenging. Elad Eldor has experienced these challenges first-hand, leading to his work writing the book "Kafka: : Troubleshooting in Production" In this episode he highlights the sources of complexity that contribute to Kafka's operational difficulties, and some of the main ways to identify and mitigate

Kafka 245

Kafka Data Lake High Quality Data SQL 245

Data Engineering Weekly

DECEMBER 24, 2023

RudderStack is the Warehouse Native CDP, built to help data teams deliver value across the entire data activation lifecycle, from collection to unification and activation. Visit rudderstack.com to learn more. Sanjeev Mohan: Unveiling the Crystal Ball: 2024 Data and AI Trends Sanjeev & Rajesh, as usual, share their excellent observations about data & AI industry trends.

Data Engineering 62

Data Engineering Data Engineer Engineering Deep Learning 62

Towards Data Science

DECEMBER 24, 2023

My learnings from Databricks customer engagements Figure 1: a technical diagram of how to write apache spark. Image by author. After working with ~15 of the largest retail organizations for the past 18 months, here are the Spark tips I commonly repeat. Throughout this post, we assume a general working knowledge of spark and it’s structure, but this post should be accessible to all levels of spark.

Scala 85

Scala SQL Java Python 85

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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