Fri.Jul 26, 2024

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How to implement data quality checks with greatexpectations

Start Data Engineering

1. Introduction 2. Project overview 3. Check your data before making it available to end-users; Write-Audit-Publish(WAP) pattern 4. TL;DR: How the greatexpectations library works 4.1. greatexpectations quick setup 5. From an implementation perspective, there are four types of tests 5.1. Running checks on one dataset 5.2. Checks involving the current dataset and its historical data 5.3.

Datasets 208
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Bayesian Thinking in Modern Data Science

KDnuggets

Discover how Bayesian thinking transforms decision-making with its unique approach to updating initial beliefs with new evidence.

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Data News — Week 24.30

Christophe Blefari

Tallinn ( credits ) Dear members, it's Summer Data News, the only news you can consume by the pool, the beach or at the office—if you're not lucky. This week, I'm writing from the Baltics, nomading a bit in Eastern and Northern Europe. I'm pleased to announce that we have successfully closed the CfP for Forward Data Conf, we received nearly 100 submissions and the program committee is currently reviewing all submissions.

MySQL 130
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A Framework for Multi-Model Forecasting on Databricks

databricks

Introduction Time series forecasting serves as the foundation for inventory and demand management in most enterprises. Using data from past periods along with.

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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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Mainframe History: How Mainframe Computers Have Changed Over the Years

Precisely

Mainframes have one of the longest histories of any kind of computing technology that is still used today. In fact, mainframe history shows the fast-evolving landscape of technology, few innovations have left as profound a mark as mainframe computers. From their inception to the sophisticated systems of today, mainframes have continuously adapted to meet the ever-growing demands of business operations.

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Odin: Uber’s Stateful Platform

Uber Engineering

Explore Odin, Uber’s stateful platform for managing all types of databases. It is a technology-agnostic, intent-based system that has dramatically improved the operational throughput of underlying hosts and databases company-wide.

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Radical Simplicity in Data Engineering

Towards Data Science

Learn from Software Engineers and Discover the Joy of ‘Worse is Better’ Thinking source: unsplash.com Recently, I have had the fortune of speaking to a number of data engineers and data architects about the problems they face with data in their businesses. The main pain points I heard time and time again were: Not knowing why something broke Getting burnt with high cloud compute costs Taking too long to build data solutions/complete data projects Needing expertise on many tools and technologies

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Pickup in 3 minutes: Uber’s implementation of Live Activity on iOS

Uber Engineering

From WWDC reveal to delivery, discover how we tackled new tech, design challenges, and tight timelines to enhance rider & driver experiences with Live Activity® from Apple.

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The Engineering Behind Booking.com’s Ranking Platform | A System Overview

Booking.com Engineering

The Engineering Behind High-Performance Ranking Platform: A System Overview An Introduction Booking.com employs sophisticated ranking to optimize search results for each user. The system uses advanced machine learning algorithms and leverages extensive data, including user behavior, preferences, and past interactions, to tailor hotel listings and travel recommendations.

Systems 42