Embedding analytics in applications is a smart way to expose insights and decision-making capabilities directly in employee workflow and customer-facing apps.
Stories by Isaac Sacolick
Multiple options make machine learning available to professional data scientists, citizen data analysts and software developers.
When teams are split between home and office, establishing some ground rules will keep projects moving efficiently.
As your data evolves, you need a way to track the who, what, when, why, and how of those changes. You need a data lineage system.
So little time, so many ways tech decisions can go wrong. To make wise choices, don’t let these decision-making anti-patterns get in the way.
Once upon a time, business sponsors pestered development teams about when a feature would be done or a release ready for deployment.
Virtualisation of APIs and application services supports robust and earlier testing, an important part of application modernisation.
Multi-cloud architecture can be expensive and complex. These tools can facilitate provisioning, automation and resiliency.
With every organisation generating and accessing multiple data sources, an integration platform ensures every team has the data they need.
IFTTT platforms, TDD methodologies and integration platforms make life easier for developers seeking to prototype and test their own APIs.
These platforms offer great potential, but capabilities vary widely. Take time to study the options.
Integrating design principles into the development process improves customer and user experiences.
Experts share how software development teams can ‘shift security left’ and improve governance levels in the process.
Developers may come and go, but good documentation lasts forever—and is valuable to many different audiences.
Sift through unstructured text with cloud-native products, machine learning tools, or specialised text analytics programs.