Sibanjan Das offers up a tutorial for building a web-based cluster and prediction analysis application through using R with the open source Shiny framework. Oh yeah, and he embedded the app directly into this DZone article... shine on you crazy data scientist.
Chatbots continue to work their way into ever-more solutions, but how should we evaluate their effectiveness? In this post we take a look at a potential framework for doing just that.
Data-driven testing facilitates test procedures, demonstrates more capability in discovering bugs, and ensures quality with logical input to assure successful deployment.
Nulls and the dreaded NPE can be awful, but by maintaining encapsulation, keeping your code simple, and using nulls only in certain situations, you can come out on top.
You can customize a Mule caching strategy so that the Mule cache scope actions can operate on the Redis data store. You can also try other third-party caching frameworks.
If you have Redis, Node.js, and the Heroku toolbelt installed on your machine, then you've got everything you need to build a real-time chat application.
MongoDB's views are a recent innovation that help with both data security and abstraction. They don't use disk space or a physical schema, so see how they work!
When it comes to dynamic SQL, all jOOQ statements are dynamic. You can also look to functional programming-optimized tricks like the Strategy Pattern to help.
In the final article to his comprehensive series on learning Oracle JET, Chris Muir goes over the Oracle JET Common Model & Collection API, a client-side JavaScript API for accessing remote REST web services and plugging them into our JET UI components.
Using a poor-quality server wastes everyone's time because the build takes too long to finish, resulting in intermittent test results and frustrated engineers.
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