The way we write, ship, and maintain software today has evolved drastically in the last few years. How we consume underlying infrastructure to run our software has matured significantly, in that we have seen a transition from bare metal to virtual machines to containers to micro-VMs.
Kotlin Multiplatform apps are a great option for big projects. They allow us to unify the business logic under a Kotlin module while using the latest perks of each platform’s individual UI, significantly reducing development costs. Debugging in Kotlin Multiplatform is easy, as you can use typical tools like adding breakpoints and printing logs in the console – and in Bugfender. Continue reading for a full tutorial. KMM stands for Kotlin Multiplatform Mobile.
Business Intelligence (BI) tools allow businesses to gather, process and analyse large amounts of data so that they are able to make decisions and see opportunities as well as visualise and report on key metrics for Stakeholders. The range of Business Intelligence tools available to use is an ever-expanding list with newcomers to the market appearing every year.
With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.
As a product feature for your app, embedded analytics is undoubtedly a valuable tool. But historically, many product managers and software developers have approached it as a standalone capability. This has led to dashboards and reporting modules added as an afterthought, rather than as a founding strategic component of the core application.
We’ve all heard the war stories born out of wrong data: These stories don’t just make you and your company look like fools, they also cause great economic damages. And the more your enterprise relies on data, the greater the potential for harm. Here, we take a look at what data quality is and how the entire data quality management process can be improved.
