Systems | Development | Analytics | API | Testing

How to make a 'Visionary' product - A product design perspective

Last week it was announced that Yellowfin jumped to Visionary in the Gartner 2020 Magic Quadrant for Analytics and BI Platforms. Toot toot! This is a massive achievement for the entire Yellowfin team putting us in the same room as products by the biggest players on the planet. What makes it so special is that we are a privately funded, Melbourne based organisation smashing it against huge, cashed-up tech giants.

Unravel Introduces Workload Migration and Cost Analytics Solution for Azure Databricks, now available on Azure Marketplace

Fresh off a new funding round which includes strategic cloud partner Microsoft, Databricks continues to make huge strides in its mission to ease Spark complexity and simplify analytics through its Unified Analytics Platform. Databricks has also graduated from “visionary” to “leader” in the latest Gartner Magic Quadrant for Data Science and Machine Learning Platforms in 2020.

Business Monitoring: If You Can't Measure It, You Can't Improve It

“If you can’t measure it, you can’t improve it” …this quote by Peter Drucker and the philosophy behind it is a key driving force behind modern management and the introduction of BI solutions to support the scaling and increased complexity of businesses. Analytics tools were developed to enable metric measurement and business monitoring across large scale, complex systems and to enable continuous improvements of business performance.

Why Data Chain of Custody is Essential to Reducing Product Liability Risks

When a market grows as quickly as implantable medical devices, set to top a staggering $153.8 billion by 2026, the potential risk to patients can rise as well. As implantable medical devices proliferate, so do the number of costly, life-threatening, and reputation-tarnishing recalls. A single large recall can account for millions of device units.

A Comprehensive Guide to Migrating from Python 2 (Legacy Python) to Python 3

Python powers many applications we use in our day-to-day like Reddit, Instagram, Dropbox, and Spotify. The adoption of Python 3 has been a subject of debate in the Python community. While Python 3 has been out for more than a decade now, there wasn’t much incentive to migrate from the stable Python 2.7 in the earlier releases. If you’re still running on legacy python, it’s high time to migrate as it has reached the end of its life since Jan 2020.

Introducing Notifications API to Automate Notification Settings Across Projects

At Rollbar we love workflow automation. With our new Notifications API, you can automate setting up of custom notification rules for all your Rollbar projects. As more of our customers switch to microservices, we wanted to build a programmatic way to set up these rules for multiple projects or services in just a few seconds, without having to go to the UI.

Effective Profiling in Google Chrome

This blog post will explain how to effectively profile your website so that you can deal with performance pain points. We’ll go through the two most used tools in Google Chrome for profiling: Imagine that you optimized your backend and everything is running smoothly. However, for some reason, the load time of your pages is still unreasonably high. Your users might be experiencing sluggish UI and long load times. This post will help you sort these issues out.

Code coverage for Swift Package Manager based apps

The Swift Package Manager allows you to create standalone Swift applications both on Linux and macOS. You can build and run these apps and you have the ability to write unit tests for your codebase. Xcode ships with the XCTest framework, but you may not know that this is an open-source library. It's available on every single platform where you can install Swift.

What is Continuous Application Improvement?

CAI stands for Continuous Application Improvement. It is a software improvement process that is implemented at each step of the SDLC, ensuring immediate feedback at each step rather than waiting till risk levels and impact has gone up. When you implement CAI you shift your improvement process as far left as possible and you catch software bugs and performance problems where they are introduced, eliminating countless hours of time spent chasing issues.