The AI business landscape
A data-driven analysis of companies that are adopting artificial intelligence.
Data
Our take on the ideas, information, and tools that make data work.
Structured streaming comes to Apache Spark 2.0
The O’Reilly Data Show Podcast: Michael Armbrust on enabling users to perform streaming analytics, without having to reason about streaming.
Building and deploying large-scale machine learning applications
The O’Reilly Data Show Podcast: Danny Bickson on recommenders, data science, and applications of machine learning.
Semi-supervised, unsupervised, and adaptive algorithms for large-scale time series
The O’Reilly Data Show Podcast: Ira Cohen on developing machine learning tools for a broad range of real-time applications.
Practical machine learning techniques for building intelligent applications
The O’Reilly Data Show Podcast: Mikio Braun on practical data science, deep neural networks, machine learning, and AI.
Keynotes from Strata + Hadoop World in San Jose 2016
Watch full keynotes covering data science, data tools, enterprise adoption and more. From Strata + Hadoop World in San Jose 2016.
The big data market
A data-driven analysis of companies using Hadoop, Spark, data science, and machine learning.
Democratizing business analytics
The O’Reilly Data Show Podcast: Duncan Ross on the evolution of analytics, data mining, and data philanthropy.
Stream processing and messaging systems for the IoT age
The O’Reilly Data Show podcast: M.C. Srivas on streaming, enterprise grade systems, the Internet of Things, and data for social good.
Using Apache Spark to predict attack vectors among billions of users and trillions of events
The O’Reilly Data Show podcast: Fang Yu on data science in security, unsupervised learning, and Apache Spark.
Metadata services can lead to performance and organizational improvements
The O’Reilly Data Show podcast: Joe Hellerstein on data wrangling, distributed systems, and metadata services.
Insightful applications: The next inflection in big data
One investor’s retrospective of data analytics over the last 25 years.
Building a business that combines human experts and data science
The O’Reilly Data Show podcast: Eric Colson on algorithms, human computation, and building data science teams.
Streaming 102: The world beyond batch
The what, where, when, and how of unbounded data processing.
Is 2016 the year you let robots manage your money?
The O’Reilly Data Show podcast: Vasant Dhar on the race to build “big data machines” in financial investing.
When building an enterprise data strategy, consider “why?” before “how?”
Roadmaps should be driven by business goals, not technology.
Investing in big data technologies
The O’Reilly Data Show podcast: A fireside chat with Ben Horowitz, plus Reynold Xin on the rise of Apache Spark in China.
How to think like a data scientist
Using induction to test your hypotheses
Building a scalable platform for streaming updates and analytics
The O’Reilly Data Show podcast: Evan Chan on the early days of Spark+Cassandra, FiloDB, and cloud computing.
Programming, oaths, and users
The Programmer's Oath is missing one essential element: the customer.
Graph databases are powering mission-critical applications
The O’Reilly Data Show Podcast: Emil Eifrem on popular applications of graph technologies, cloud computing, and company culture.
Exploring the process of insight generation
True insights require a measurable action plan and domain knowledge.
What to look for in a data scientist
How an algorithm is to a data scientist what a compound microscope is to a biologist.
Jai Ranganathan on architecting big data applications in the cloud
The O’Reilly Data Show podcast: The Hadoop ecosystem, the recent surge in interest in all things real time, and developments in hardware.