In our modern world, accelerating the process of extracting insights from data is a complex challenge. Exacerbating this task are colossal data volumes, the expansion and use of multiple cloud platforms, and the increasing demands for self-service in a way that maintains compliance. Enterprises attempting to tackle the problem encounter various forms of friction everywhere they turn.

The COVID-19 global pandemic has changed the ways we work, including how we use data, forever. Amidst the crisis, the analytics industry is experiencing its own paradigm shift.

During the process of turning data into insights, the most compelling data often comes with an added responsibility—the need to protect the people whose lives are caught up in that data. Plenty of data sets include sensitive information, and it’s the duty of every organization, down to each individual, to ensure that sensitive information is handled appropriately.

We rely on advanced data platforms that extract data from multiple sources, clean it, and save it so data scientists and analysts can gain insights from data. Data seems to flow seamlessly from one location to another, supporting our data-driven decision-making. The entire system runs smoothly because the engineering operations under the hood are correctly set and maintained.

In software development, a fail-fast system is a tool that will notify when a failure is likely to occur. The philosophy of the fail-fast principle is formed around the idea that a system should stop normal operations rather than trying to continue working around a flawed piece of code. The fail-fast principle makes software bugs easier to detect earlier in the development cycle.

Ably is an enterprise-grade pub/sub messaging platform with a suite of integrated services to deliver realtime experiences like interactive learning, logistics GPS tracking, and live sports updates.

In this post, I’ll take a close look at asynchronous queries in Recoil. I’ll show you what the library is capable of and how it blends seamlessly with React. Let’s get going!

Many organizations are using Gitflow as a branching model for their use of Git and Github Checks to monitor their testing of code changes. This article highlights how following the Gitflow process for a Hotfix can produce unexpected results when using Github Checks and explains why this edge case occurs.

Any software development project will almost certainly have through several tests by the time it is finished, especially in an Agile testing environment where testing and development occur simultaneously. But, no matter how many tests you've conducted, there's really only one way to tell if your software can handle the actual demands your army of end-users will be throwing on it once it's nearly finished. It's known as load testing.

Following best practices when logging helps make sure they contain the right information when needed. Some common best practices for logging errors in.NET are listed below.