Inside-Opensource.org

AHA has bigger ambitions to facilitate research and is looking to develop a “data discovery platform”.

There’s a logical hierarchy of needs for developing a big data strategy.

Inventors are taking on the world's biggest problems with tenacity and creativity.

This post intends to demonstrate how easy can be to build a stream processing application with Kafka Streams.

See what’s happened with Apache Spark in the last couple of weeks

Databricks has been partnering with enterprises and government agencies to securely process mission-critical workloads with Spark.

O’Reilly Media has released a new salary survey.

Big data is now receiving the same treatment as relational data.

Luca Canali of CERN investigates performance improvements in Apache Spark 2.0 from whole-stage code generation using flame graphs.

“Cloud” means different things to different marketers.

If you’re looking to learn data science – quickly – then you’re in luck.

The adoption of big data processing and analytics is pervasive across almost all industries.

The marketing message was all about huge scalability and the potential for big data.

What is a natural way for people to interact with technology.

Most mainstream consumers are still put off by the price and size of the printers.

There is automation. But the machine learning process is never-ending.

The funds will support SAP's creation of IoT development labs around the world and the launch of a new product line.

The new Parallels 12 does the job well.

A Buyer’s Guide from ESG Global

Benchmark general partner Bill Gurley said he’s still worried about a bubble.

Consistent quality data is cited as the number one challenge organizations face to realizing the full potential from analytics.

The results show that the Spark community is still growing fast.

Signal is favored by many in the security community because the open nature of the software allows others to review its code.

HTML5 all the way. But nor for ads. So keep those malware shields up.

For machine learning - they say their cloud products will free data scientists and developers from implementation details so they can focus on business logic.

The journey will be a balancing act for avoiding conflict with the analytics software partners that have been pillars of its ecosystem.

Apple is increasingly acquiring firms with expertise in machine learning and artificial intelligence.

You need to have motivation and be able to code and problem solve well. That's about it.

It is a transcript of a conversation between Dr. Robin Bloor and Rick Glick.

Data science has early roots in scientists efforts to understand human intelligence and create artificial intelligence.