Remove Data Pipeline Remove Engineering Remove Pipeline-centric
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Snowflake’s New Python API Empowers Data Engineers to Build Modern Data Pipelines with Ease

Snowflake

This traditional SQL-centric approach often challenged data engineers working in a Python environment, requiring context-switching and limiting the full potential of Python’s rich libraries and frameworks. To get started, explore the comprehensive API documentation , which will guide you through every step.

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Elevating Productivity: Cloudera Data Engineering Brings External IDE Connectivity to Apache Spark

Cloudera

As advanced analytics and AI continue to drive enterprise strategy, leaders are tasked with building flexible, resilient data pipelines that accelerate trusted insights. A New Level of Productivity with Remote Access The new Cloudera Data Engineering 1.23 Why Cloudera Data Engineering?

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Improve Data Quality Through Engineering Rigor And Business Engagement With Synq

Data Engineering Podcast

Petr shares his journey from being an engineer to founding Synq, emphasizing the importance of treating data systems with the same rigor as engineering systems. He discusses the challenges and solutions in data reliability, including the need for transparency and ownership in data systems.

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Data Engineering Weekly #186

Data Engineering Weekly

Take Astro (the fully managed Airflow solution) for a test drive today and unlock a suite of features designed to simplify, optimize, and scale your data pipelines. Try For Free → Conference Alert: Data Engineering for AI/ML This is a virtual conference at the intersection of Data and AI.

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Data Engineering Weekly #196

Data Engineering Weekly

The blog emphasizes the importance of starting with a clear client focus to avoid over-engineering and ensure user-centric development. Sampling is an obvious strategy for data size, but the layered approach and dynamic inclusion of dependencies are some key techniques I learned with the case study.

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Introducing CDP Data Engineering: Purpose Built Tooling For Accelerating Data Pipelines

Cloudera

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

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Data Engineering Weekly #161

Data Engineering Weekly

There will be food, networking, and real-world talks around data engineering. Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 4) Building Data Products and why should you?