AI is no longer just a buzzword – it’s the driving force behind the next wave of innovation in the software industry. Companies that embrace AI today are automating tasks, boosting efficiency, and unlocking new levels of productivity. However, as revolutionary as AI is, adopting it within technical software teams isn’t without its challenges. From skill shortages to navigating ethical dilemmas, businesses face a steep adoption curve.

Forrester’s Global Retail E-Commerce Forecast, 2024 to 2028, predicts global online retail sales will rise from $4.4 trillion in 2023 to $6.8 trillion by 2028. Despite this increase, 76% of retail sales ($21.9 trillion) will remain offline by 2028. To remain competitive, retailers are enhancing their omnichannel strategies by seamlessly integrating online and offline experiences.

The world of quality assurance (QA) has changed, and there’s no turning back. Digital transformation is driving the need to produce high-quality software faster, while also keeping costs under control. The old idea of choosing between speed, cost-efficiency, or quality? That’s out the window. Today, you need all three to succeed, and they’ve got to work together.

Learn how CHS Inc., Pitney Bowes and Envision Pharma use Fivetran for high-volume database replication to streamline operations, drive growth and save money.

In today’s digital landscape, maintaining a smooth user experience is essential. Websites and applications are expected to perform reliably and quickly, with minimal interruptions. One effective approach to enhancing user experience is synthetic monitoring, which uses simulated transactions to test performance. This article will delve into how synthetic monitoring improves user experience and highlight its benefits, along with code examples for implementation.

Containerized microservices are essential to cloud migration and digital transformation plans. Do you have a clear picture of what containerized microservices are and why they’re important? In this guide, you'll learn about containers, microservices, and how they work together. First up is a bit of history that explains how the need for containers came to be. Here's the key things to know about containerized microservices.

Took me years to finally get a Roomba (those robot vacuums from iRobot that have been around since 2002). I was pretty skeptical about how well it would clean and how smart and autonomous it really was. My wife was on board on the benefits from the start, but I needed some convincing. After plenty of back-and-forth (and my wife’s persistence), we went for it. Honestly, the benefits weren’t obvious to me from the start.

In today's data-driven landscape, data analysts rely on powerful database management tools to organize, query, and extract insights from vast datasets. With a multitude of options, choosing the right tool can significantly impact efficiency and performance. Tools like MySQL Workbench, SQL Server Management Studio, and Google BigQuery provide robust platforms for relational data management, while options such as MongoDB Compass cater to unstructured data needs.