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Abstracting column access in PySpark with Proxy design pattern

Waitingforcode

One of the biggest changes for PySpark has been the DataFrame API. It greatly reduces the JVM-to-PVM communication overhead and improves the performance. However, it also complexities the code. Probably, some of you have already seen, written, or worked with the code like this.

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Implementing a Dimensional Data Warehouse with Databricks SQL: Part 2

databricks

As organizations consolidate analytics workloads to Databricks, they often need to adapt traditional data warehouse techniques.

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Securing Machine Learning Applications with Authentication and User Management

KDnuggets

A step-by-step guide to securing a FastAPI machine learning applications' endpoints with native authentication and user management.

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Unapologetically Technical Episode 20 – Shane Murray

Jesse Anderson

I n this episode of Unapologetically Technical, I interview Shane Murray, Field CTO at Monte Carlo Data. Shane shares his compelling journey from studying math and finance in Sydney, Australia, to leading AI strategy at a major data observability company in New York. We explore his early work in choice modeling and pioneering online multivariate experimentation long before A/B testing became mainstream, including fascinating examples from cruise lines, American Express, and even cultural surpris

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A Guide to Debugging Apache Airflow® DAGs

In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs. You’ll learn how to: Create a standardized process for debugging to quickly diagnose errors in your DAGs Identify common issues with DAGs, tasks, and connections Distinguish between Airflow-relate

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Atlassian + Databricks: Unlocking Data Insights with Delta Sharing

databricks

Atlassian recently partnered with Databricks to power new data sharing capabilities from Atlassian Analytics, using the Delta Sharing protocol.

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Fixrleak: Fixing Java Resource Leaks with GenAI

Uber Engineering

Goodbye resource leaks! Learn how the FixrLeak framework leverages GenAI and AST-level analysis to automatically detect and fix resource leaks in large-scale Java applications at Uber.

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Enhancing the Python ecosystem with type checking and free threading

Engineering at Meta

Meta and Quantsight have improved key libraries in the Python Ecosystem. There is plenty more to do and we invite the community to help with our efforts. Well look at two key efforts in Pythons packaging ecosystem to make packages faster and easier to use: Unlock performance wins for developers through free-threaded Python where we leverage Python 3.13s support for concurrent programming (made possible by removing the Global Interpreter Lock (GIL)).

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Expand to New Regions with Zero Additional Egress Costs

Snowflake

Data providers want their data available to their customers, no matter where in the world or on which cloud service provider the customer is located. However, egress costs can contribute up to 70% of total data transfer costs. Providers have historically had to balance the desire to increase the availability of their data to any relevant Snowflake regions with the need to manage egress costs.

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CCM Solutions: Build or Buy for Your Business?

Precisely

Delivering seamless, personalized experiences for customers across channels continues to be a priority for organizations across industries. To make this goal a reality, they seek out powerful customer communications management (CCM) solutions. However, theres often a debate on whether to build a custom in-house solution or purchase an enterprise-grade platform.

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Mastering NumPy’s Universal Functions for Fast Array Computation

KDnuggets

Master element-wise operations, comparisons, logic, aggregation, and broadcasting using NumPy ufuncs for high-performance array processing.

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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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Migrating Uber’s Compute Platform to Kubernetes: A Technical Journey

Uber Engineering

Migrating tech stacks at Ubers scale isnt easy. Learn how we migrated our stateless container orchestration platform to Kubernetes and operate it at a scale of 3 million cores with 1.5 million pod launches daily.

IT 55
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Data Engineering Interview Series #3: SQL

Start Data Engineering

1. Introduction 2. Step-by-step process to solve any SQL interview question 2.1. Define what the input data is and how they are related 2.2. Understand the input table’s grain, foreign keys, and how they relate to each other 2.3. Define the dimensions and metrics required for the output 2.4. Filter/Join/Group by input columns to get the output dimension and metrics 3.

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Navigating Your Netezza to Databricks Migration: Tips for a Seamless Transition

databricks

Why migrate from Netezza to Databricks? The limitations of traditional enterprise data warehouse (EDW) appliances like Netezza are becoming increasingly apparent.

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9 Amazing Application of data engineering in real life

Edureka

When you purchase online, do you ever find yourself pondering how your tastes get changed into suggestions for products that are uniquely suited to you? Or how self-driving cars get through very complicated situations with amazing accuracy? These are the ways that data engineering improves our lives in the real world. The field of data engineering turns unstructured data into ideas that can be used to change businesses and our lives.

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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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AI data collection guide

InData Labs

Artificial intelligence services have been a hot topic for the last decade. It is hard to find an area or industry nowadays that hasnt at least tried to use this relatively new tool in its work. However, there is one thing that makes it possible for AI to exist. This thing is DATA. Without high-quality. AI data collection guide InData Labs.

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Sol Rashidi on Why Most AI Strategies Fail—and What Great Data Leaders Get Right

Striim

Get More Insights In Your Inbox Sol Rashidi has built AI, data, and digital strategies inside some of the worlds biggest companiesand shes seen the same mistakes play out again and again. In this episode, she unpacks why AI initiatives often stall, how executives misread what transformation really requires, and why the future of AI success isnt technicalits cultural.

Data 52
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Snowflake Invests in RightRev to Add Revenue Accounting Automation to the AI Data Cloud

Snowflake

Consumption-based pricing helps Snowflake balance the power of true cloud elasticity with clear visibility into usage and spending. According to The State of Usage-Based Pricing: Second Edition , three out of five SaaS companies now incorporate some form of usage-based pricing into their offerings. Thats why Snowflake Ventures is reinvesting in our partner RightRev , a cloud-based revenue recognition management platform created to facilitate improved financial reporting processes, specifically

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Navigating the SQL Server to Databricks Migration: Tips for a Seamless Transition

databricks

The imperative for modernization Traditional database solutions like SQL Server have struggled to keep up with the demands of modern data workloads due to a

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How to Modernize Manufacturing Without Losing Control

Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives

Manufacturing is evolving, and the right technology can empower—not replace—your workforce. Smart automation and AI-driven software are revolutionizing decision-making, optimizing processes, and improving efficiency. But how do you implement these tools with confidence and ensure they complement human expertise rather than override it? Join industry expert Andrew Skoog as he explores how manufacturers can leverage automation to enhance operations, streamline workflows, and make smarter, data-dri

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Data Engineering Weekly #220

Data Engineering Weekly

Dagster Running Dagster: Our Open Platform We’re pulling back the curtain. Join us on May 13 for a live deep dive into how Dagster Labs runs Dagster in production. One of our lead data engineers will walk through our real-world implementation, architecture decisions, and the lessons we've learned scaling the platform. Register now Editor’s Note: OpenXData Conference - 2025 - A Free Virtual Event A free virtual event on open data architectures - Iceberg, Hudi, lakehouses, query engine

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Real-Time Spatial Temporal Forecasting @ Lyft

Lyft Engineering

Written by Josh Xi & Rakesh Kumar atLyft. From real-time rider pricing and driver incentives to long-term budget allocation and strategic planning, forecasting at Lyft plays a pivotal role in providing a foresight of our market conditions for efficient operations and facilitating millions of rides daily across North America. This article explores real-time spatial temporal forecasting models and system designs used for predicting market conditions, focusing on how their complexity and rapid

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Stream ServiceNow Data to Google BigQuery

Striim

Introduction This recipe shows how you can build a data pipeline to read data from ServiceNow and write to BigQuery. Striim’s ServiceNow Reader will first read the existing tables from the configured ServiceNow dataset and then write them to the target BigQuery project using the BigQuery Writer, a process called “initial load” in Striim and “historical sync” or “initial snapshot” by others.

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How Snowflake Is Driving the Future of Auto Innovation

Snowflake

The automotive industry has undergone a seismic transformation over the last several decades. In 2005, most vehicles were mechanically sophisticated but had limited digital capabilities and integrations. Today, the automobile is a computer on wheels: software-defined, cloud-connected, increasingly autonomous and continuously evolving through over-the-air (OTA) updates.

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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Upskill yourself and your teams at Data+AI Summit

databricks

We are experiencing an unprecedented pace of technological innovation driven by AI and data.

Data 66
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ArcGIS Pro on Windows 365 GPU-enabled Cloud PCs: Delivering High-Performance GIS Anywhere

ArcGIS

ArcGIS Pro on Windows 365 GPU-enabled Cloud PCs

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3 Excellent Practical Generative AI Courses

KDnuggets

Learn to build AI agents, fine-tune reasoning models, and master practical AI skills with these courses.

Building 144
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6 Real-World ETL Use Cases with Estuary Flow

Seattle Data Guy

After working in data for over a decade, one thing that remains the same is the need to create data pipelines. Whether you call them ETLs/ELTs or something else, companies need to move and process data for analytics. The question becomes how companies are actually building their data pipelines. What ETL tools are they actually… Read more The post 6 Real-World ETL Use Cases with Estuary Flow appeared first on Seattle Data Guy.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Snowflake Invests in Theom to Automate Data Protection

Snowflake

In today's complex enterprise environments, managing data security is a daunting challenge. Organizations are grappling with a growing number of data stores, data sharing, increasing use of data for AI and increasingly sophisticated threats. This complexity necessitates a shift toward automated, AI-driven solutions that simplify security governance and accelerate threat detection.

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From Warehouse to Lakehouse: Migration Approaches to Databricks

databricks

Before making architectural decisions, its worth revisiting the broader migration strategy.

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Accelerating GPU indexes in Faiss with NVIDIA cuVS

Engineering at Meta

Meta and NVIDIA collaborated to accelerate vector search on GPUs by integrating NVIDIA cuVS into Faiss v1.10 , Metas open source library for similarity search. This new implementation of cuVS will be more performant than classic GPU-accelerated search in some areas. For inverted file (IVF) indexing, NVIDIA cuVS outperforms classical GPU-accelerated IVF build times by up to 4.7x; and search latency is reduced by as much as 8.1x.

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Getting Started With a Career in Data Science

KDnuggets

Breaking into data science has never been easy. In this tutorial, well make your life easier by providing you with a step-by-step roadmap for data science beginners.

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The Ultimate Guide to Apache Airflow DAGS

With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to: Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to Write DAGs that adapt to your data at runtime and set up alerts and notifications Scale you