Data Engineering Podcast

JUNE 17, 2017

Summary Yelp needs to be able to consume and process all of the user interactions that happen in their platform in as close to real-time as possible. To achieve that goal they embarked on a journey to refactor their monolithic architecture to be more modular and modern, and then they open sourced it! In this episode Justin Cunningham joins me to discuss the decisions they made and the lessons they learned in the process, including what worked, what didn’t, and what he would do differently

Data Pipeline 100

Data Pipeline Kafka Business Intelligence Architecture 100

Uber Engineering

JUNE 19, 2017

Uber is developing a payment platform for India that enables operations teams to more seamlessly collect and distribute cash and digital wallet payments to drivers. In this article, San Francisco-based software engineer Yijun Liu reflects on his experiences working with … The post Re-Architecting Cash and Digital Wallet Payments for India with Uber Engineering appeared first on Uber Engineering Blog.

Engineering 96

Engineering Software Engineer Software Engineering Business Intelligence 96

Zalando Engineering

JUNE 20, 2017

A lot of time has passed at Zalando since the first services were started backed by PostgreSQL 9.0-rc1. Despite the adoption of other technologies, PostgreSQL remains the preferred relational database for most engineers around. You can follow some of the developments around PostgreSQL on the blog and also on GitHub where we share most of our PostgreSQL-related tooling.

PostgreSQL 40

PostgreSQL AWS Relational Database Database 40

ProjectPro

JUNE 22, 2017

What is a Hadoop Cluster? In general, a computer cluster is a collection of various computers that work collectively as a single system. “A hadoop cluster is a collection of independent components connected through a dedicated network to work as a single centralized data processing resource. “ “A hadoop cluster can be referred to as a computational computer cluster for storing and analysing big data (structured, semi-structured and unstructured) in a distributed environment.

Hadoop 52

Hadoop IT Data Analysis Big Data 52

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science