What is Artificial Intelligence?
Mike Loukides and Ben Lorica examine factors that have made AI a hot topic in recent years, today's successful AI systems, and where AI may be headed.
Our take on the ideas, information, and tools that make data work.
Ideas
Analyzing data in the Internet of Things
This report dives into the IoT industry through a series of illuminating talks and case studies presented at 2015 Strata + Hadoop World Conferences in San Jose, New York, and Singapore.
10 signs of data science maturity
How well prepared is your organization to innovate, using data science? In this report, two leading data scientists at Booz Allen Hamilton describe 10 characteristics of a mature data science capability.
5 secrets for writing the perfect data scientist resume
No hype. No fluff. Just skills.
Hybrid transactional/analytic systems and the quest for database nirvana
The O’Reilly Data Show Podcast: Rohit Jain on the challenges of hybrid data management systems.
Prophecies and predictive models: How a 3D approach to data transforms your business
Tricia Wang explores the application of “thick data” gathered through qualitative methods.
2015 Data Science Salary Survey
Tools, trends, what pays (and what doesn’t) for data professionals.
Drawing insights from imperfection: A year of Dear Data
Stefanie Posavec discusses the insights she gained spending a year on her intensive Dear Data project.
Learning
Runnable code
Making Sense of Stream Processing
Stream processing is finally coming of age. This report shows you how stream processing can make data storage and processing systems more flexible and less complex.
Video
Apache Spark 2.0: Introduction to Structured Streaming
Michael Armbrust and Tathagata Das explain updates to Spark version 2.0, demonstrating how stream processing is now more accessible with Spark SQL and DataFrame APIs.
Runnable code
Hello, TensorFlow!
Building and training your first TensorFlow graph from the ground up.
The world beyond batch: Streaming 101
A high-level tour of modern data-processing concepts.
The world beyond batch: Streaming 102
The what, where, when, and how of unbounded data processing.
Runnable code
How to build and run your first deep learning network
Step-by-step instruction on training your own neural network.
Shop
VIDEO
VIDEO
Events
Sessions
Tutorial
Architecting A Data Platform
Tutorial
Going pro in data science
Tutorial
An introduction to Apache Kafka
Session archive
Connected brains
Joseph Sirosh offers a fascinating look into how brains connected with sensors to the cloud and machine learning could revolutionize a field of medici...
Using computer vision to understand big visual data
Alyosha Efros discusses using computer vision to understand big visual data.
Thinking like a Bayesian
Julia Galef explores why Bayesian thinking is so different from what we do by default and outlines the most important principles of thinking like a Ba...
Using commerce data to fuel innovation
US Department of Commerce Deputy Secretary of Commerce Bruce Andrews explores using commerce data to fuel innovation.
People
Martin Kleppmann
Martin Kleppmann is a software engineer and entrepreneur. He has co-founded two startups including Rapportive, which was acquired by LinkedIn. At these companies he worked on various data infrastructure systems, and learnt a few things the hard way. He hopes that this book will save you from repeati...
Gwen Shapira
Gwen is a software engineer at Cloudera. She has 15 years of experience working with customers to design scalable data architectures. Working as an data warehouse DBA, ETL developer and a senior consu...
Max Shron
Max Shron runs a small data strategy consultancy in New York, working with many organizations to help them get the most out of their data. His analyses of transit, public health, and housing markets h...
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“Data is having an impact on business models and profitability. It’s hard to find a non-trivial application that doesn’t use data in a significant manner.”
— Ben Lorica, Director of Content Strategy for Data at O'Reilly Media