Tue.Mar 04, 2025

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Getting Started with Apache Arrow

Analytics Vidhya

Data is at the core of everything, from business decisions to machine learning. But processing large-scale data across different systems is often slow. Constant format conversions add processing time and memory overhead. Traditional row-based storage formats struggle to keep up with modern analytics. This leads to slower computations, higher memory usage, and performance bottlenecks.

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Apache XTable. Delta vs Iceberg vs Hudi.

Confessions of a Data Guy

The blog post reviews an Apache Incubating project called Apache XTable, which aims to provide cross-format interoperability among Delta Lake, Apache Hudi, and Apache Iceberg. Below is a concise breakdown from some time I spend playing around this this new tool and some technical observations: 1. What is Apache XTable? Not a New Format: Its […] The post Apache XTable.

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Building multimodal AI for Ray-Ban Meta glasses

Engineering at Meta

Multimodal AI models capable of processing multiple different types of inputs like speech, text, and images have been transforming user experiences in the wearables space. With our Ray-Ban Meta glasses, multimodal AI helps the glasses see what the wearer is seeing. This means anyone wearing Ray-Ban Meta glasses can ask them questions about what theyre looking at.

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dbt on Databricks.

Confessions of a Data Guy

Context and Motivation dbt (Data Build Tool): A popular open-source framework that organizes SQL transformations in a modular, version-controlled, and testable way. Databricks: A platform that unifies data engineering and data science pipelines, typically with Spark (PySpark, Scala) or SparkSQL. The post explores whether a Databricks environmentoften used for Lakehouse architecturesbenefits from dbt, especially if […] The post dbt on Databricks. appeared first on Confessions of a Data Guy.

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Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

Speaker: Tamara Fingerlin, Developer Advocate

Apache Airflow® 3.0, the most anticipated Airflow release yet, officially launched this April. As the de facto standard for data orchestration, Airflow is trusted by over 77,000 organizations to power everything from advanced analytics to production AI and MLOps. With the 3.0 release, the top-requested features from the community were delivered, including a revamped UI for easier navigation, stronger security, and greater flexibility to run tasks anywhere at any time.

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The Ultimate Guide to Building a Machine Learning Portfolio That Lands Jobs

KDnuggets

In this article, you'll learn how to create a portfolio that stands out.

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AI Use Case: Manufacturing

WeCloudData

Like many other industries, Artificial Intelligence has transformed and automated the Manufacturing domain. In manufacturing, AI enhances efficiency, accuracy, adaptability, and productivity across multiple processes by optimizing them. From predictive maintenance to generative AI applications, Artificial Intelligence is helping manufacturers gain a competitive edge.

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Beyond Legacy Detection: How AI-Driven Data Governance Surpasses Traditional Methods

Striim

Have you ever wondered how the biggest brands in the world falter when it comes to data security? Consider how AT&T, trusted by millions, experienced a breach that exposed 73 million records sensitive details like Social Security numbers, account info, and even passwords. Then theres Ticketmaster, where over 560 million records were compromised, triggering a cascade of issues including an antitrust lawsuit from the Justice Department.

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Using GPT-4.5 Without a $200 Subscription

KDnuggets

Discover the easiest and most affordable way to use and experience the new GPT-4.5 model on the OpenAI platform.

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Responsible Artificial Intelligence (RAI) Intro and an Example Issue: Outliers

Elder Research

Every stage of an analytics challenge is susceptible to error that can destroy useful results. Responsible AI guards against these hazards.

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Intersection and Union types with Java and Scala by Magnus Smith

Scott Logic

This is the third post in a series exploring types and type systems. Previous posts have looked at Algebraic Data Types with Java Variance, Phantom and Existential types in Java and Scala Intersection and Union Types with Java and Scala One of the difficult things for modern programming languages to get right is around providing flexibility when it comes to expressing complex relationships.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

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A case for QLC SSDs in the data center

Engineering at Meta

The growth of data and need for increased power efficiency are leading to innovative storage solutions. HDDs have been growing in density, but not performance, and TLC flash remains at a price point that is restrictive for scaling. QLC technology addresses these challenges by forming a middle tier between HDDs and TLC SSDs. QLC provides higher density, improved power efficiency, and better cost than existing TLC SSDs.

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Analyzing Topology Errors

ArcGIS

This article shows you how the new Migration toolset can help you analyze and resolve quality assurance issues you need to create a utility network.

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Title Launch Observability at Netflix Scale

Netflix Tech

Part 3: System Strategies and Architecture By: VarunKhaitan With special thanks to my stunning colleagues: Mallika Rao , Esmir Mesic , HugoMarques This blog post is a continuation of Part 2 , where we cleared the ambiguity around title launch observability at Netflix. In this installment, we will explore the strategies, tools, and methodologies that were employed to achieve comprehensive title observability atscale.

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