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The Recommendation System at Lyft

Lyft Engineering

This blog post focuses on the scope and the goals of the recommendation system, and explores some of the most recent changes the Rider team has made to better serve Lyft’s riders. Introduction: Scope of the Recommendation System The recommendation system covers user experiences throughout the ride journey.

Systems 87
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Introducing the 2019 Data Heroes – EMEA!

Cloudera

A Data Scientist : Organizations who show how they improved analytics, delivered new actionable intelligence, or designed systems for distributed deep learning and artificial intelligence to the organization’s business and customers. Stay tuned for March 19, 2019 as the winners are unveiled at the Luminaries dinner in Barcelona.

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Brief History of Data Engineering

Jesse Anderson

Google looked over the expanse of the growing internet and realized they’d need scalable systems. With an immutable file system like HDFS, we needed scalable databases to read and write data randomly. We lacked a scalable pub/sub system. I followed that post up in 2019 by showing that data scientists are not data engineers.

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Three Trends for Modernizing Analytics and Data Warehousing in 2019

Cloudera

Given the ubiquity of search engines like Google and now voice response systems like Alexa and Google Home, you would have thought that natural language, search-based analytics, and BI would have already become the norm in organizations. Natural Language Analysis and Streaming Data Analytics.

BI 52
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Building Trust in Public Sector AI Starts with Trusting Your Data

Cloudera

Launched in 2019, this strategy aims to position the US as a leader in AI research, development, and deployment. A breach or compromise of AI systems can have severe consequences, potentially compromising sensitive citizen data or even disrupting critical services. million), among others.

Building 105
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Automating dead code cleanup

Engineering at Meta

In our last blog post on automatic product deprecation , we talked about the complexities of product deprecations, and a solution Meta has built called the Systematic Code and Asset Removal Framework (SCARF). It leverages this analysis to submit change requests to remove this code from our systems.

Coding 129
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Revolutionizing Real-Time Streaming Processing: 4 Trillion Events Daily at LinkedIn

LinkedIn Engineering

Over time, LinkedIn's engineering team expanded the stream processing ecosystem with more proprietary tools like Brooklin , facilitating data streaming across multiple stores and messaging systems, and Venice , serving as a storage system for ingesting batch and stream processing job outputs, among others. hours to 25 minutes).

Process 119