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How to Build and Monitor Systems Using Airflow?

Analytics Vidhya

Are you looking for a way to automate and simplify the process? Imagine scheduling your ML tasks to run automatically without the need for manual […] The post How to Build and Monitor Systems Using Airflow? Airflow can help you manage your workflow and make your life easier with its monitoring and notifications features.

Systems 214
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Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable

Data Engineering Podcast

Summary Building streaming applications has gotten substantially easier over the past several years. Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. What was the process for adding full Java support in addition to SQL?

Process 182
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Building cost effective data pipelines with Python & DuckDB

Start Data Engineering

Building efficient data pipelines with DuckDB 4.1. Use DuckDB to process data, not for multiple users to access data 4.2. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Introduction 2. Project demo 3. Use DuckDB 4.4.

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Data Migration Strategies For Large Scale Systems

Data Engineering Podcast

Summary Any software system that survives long enough will require some form of migration or evolution. When that system is responsible for the data layer the process becomes more challenging. As you have gone through successive migration projects, how has that influenced the ways that you think about architecting data systems?

Systems 130
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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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Designing Data Transfer Systems That Scale

Data Engineering Podcast

Summary The first step of data pipelines is to move the data to a place where you can process and prepare it for its eventual purpose. Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor. Data lakes are notoriously complex.

Systems 130
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X-Ray Vision For Your Flink Stream Processing With Datorios

Data Engineering Podcast

Summary Streaming data processing enables new categories of data products and analytics. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling. How have the requirements of generative AI shifted the demand for streaming data systems? Data lakes are notoriously complex.

Process 147
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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Register today to save your seat! December 6th, 2023 at 11:00am PST, 2:00pm EST, 7:pm GMT