Analyses

machine learning
lightbulbs innovation leader standout winner

shortcut through a maze

Why there are no shortcuts to machine learning

As long as companies understand that good data science takes time in an enterprise, and give these people room to learn and grow, they won’t need shortcuts

wave the white flag surrender give up quit

When it comes to databases, why ‘I can’t quit you, baby’

Leaving legacy RDMSs is hard, but eventually enterprises will break free of Oracle’s and others’ last grip on their data infrastructure

security bug

Software security: There’s more to it than bug-bounty programs

Take full advantage of white-hat hackers to help you secure your code. And still do all the other security stuff you should do before you release your code

crowd tilt shift

Database shift: Start with open source but finish with AWS

AWS seems to be building natural bridges between on-premises databases like MySQL and cloud services like Amazon Aurora

usb beer bottle opener

Open source’s existential dilemma: the meaning of ‘free'

Developers once were quick to distinguish open source as “free as in freedom, not free as in beer.” Today, as GitHub shows, they demand the beer but are nonchalant about the freedom

forked paths forking paths trails

The Kubernetes ‘fork’: Open source purists miss the point

Is Red Hat’s OpenShift a fork of Kubernetes? No, but it still shouldn’t matter if it were

database futuristic technology

The era of the cloud database has finally begun

Enterprises are waking up to discover that their database needs have changed dramatically—and that the old-school RDBMS is no longer the best tool

chess competition with one piece left standing

Database decisions: AWS has changed the game for IT

Enterprises are figuring out that they likely need different database engines to power different parts of their applications. AWS has figured that out, too

hello my name is open source nametag

Open source isn’t the community you think it is

The irony is that what makes open source work—and differ from commercial software—is that only a few developers do the major work on any project

artificially intelligent, robotic worker

How to get started with AI—before it’s too late

Put these five prerequisites in place so you can actually execute on your artificial intelligence strategy

young girls hiding hide and seek tree game

Sensors and machine learning: How applications can see, hear, feel, smell, and taste

All five senses take the form of some kind of sensor and some kind of mathematical algorithm, usually a supervised machine learning algorithm and a model

data hole bodies fall tumble code people silhouettes

5 common pitfalls of CI/CD—and how to avoid them

What’s the secret to devops success? Start with continuous integration and continuous deployment

cloud data binary serverless

Skip containers and do serverless computing instead

Container technologies like Docker are very powerful, but require talent you can’t get. Serverless computing provides the same benefits—with talent you can actually get

17 open source table laptop group

Who really contributes to open source

New data debunks several myths around which companies lead in open source contributions

open door with sunlight shining through

20 years on, open source hasn’t changed the world as promised

Most code remains closed and proprietary, even though open source now dominates enterprise platforms. How can that be?

cloud computing concept

Google Cloud Platform’s secret sauce: Its time is now

Google’s biggest strength is helping enterprises “run like Google”—something that even old-school companies have discovered they can now do

hipster running with laptop

Why old-school PostgreSQL is so hip again

Postgres is old as dirt, yet over the past five years it has panned out as pure gold

overflowing trash can with balled up paper

No, you shouldn’t keep all that data forever

Most of your old data is useless trash. So throw it away, rather than spend all the time and money hoping AI will figure something out about it

Load More