Keep track of new connectors and product releases.

Whether you love, hate or remain indifferent towards data, it’s impossible to deny its importance in today’s business landscape. Businesses across all sectors and industries collect data and perform data analysis, to better understand their customers and business processes, in an effort to boost productivity, reduce expenditure and gain competitive advantage.

Bun and Node.js are two JavaScript runtime technologies to run JavaScript on the server. Node.js is the undisputed king of server-side development with JavaScript, but Bun has gained popularity thanks to its unbelievable performance capabilities. The real question is, though: does it really make sense to use Bun instead of Node.js? Let's learn about Bun and Node.js, dig into their characteristics, and explore some scenarios where Bun can be a better alternative to Node.js.

In today’s digital age, citizens expect seamless interactions with government agencies, mirroring the efficiency and user-friendliness they encounter in the private sector. However, achieving exceptional citizen experience (CX) requires routine testing and close attention to software quality and performance. As agencies navigate the complexities of delivering digitized services, continuous automated testing (CAT) is a game-changer in enhancing CX while maintaining speed and reliability.

In modern web applications, real-time communication has become more than a feature: it's gradually evolved into a necessity. Users expect instant updates, live interactions, and dynamic content. In Rails applications, Action Cable has long been the go-to solution, harnessing WebSockets to fulfill these demands. In this article, we introduce: Let's get started!

As the wave of AI sweeps through the technology landscape, many have hopped on board. Interestingly enough, and often overlooked, is that many AI capabilities are served through APIs. Fancy user interfaces integrate with the actual mechanisms where the magic happens: the APIs. So, when generating revenue through AI platforms, the APIs drive the revenue.

API (application programming interface) document works as a developer’s compass for navigating complex services. In this guide, we provide straightforward insights into crafting excellent API documentation. At the end of this article, you will know how to succeed as both creators and consumers of APIs through effective documentation.

Understanding how to make a GET request to an API using Python is an essential skill for developers. This article will guide you through the process, demonstrating how to use Python’s ‘requests’ library to fetch data, handle the full JSON object in response, and manage API errors efficiently. Step into the practical world of Python GET API calls without any detours.

Let’s pose a hypothetical scenario. You're the API product owner at the Paris, Texas Regional Airport. You're in charge of two main APIs: Flights API and Scheduling API. Flights API is primarily used by local research institutions that are interested in read-only access to information about departures and arrivals. Scheduling API is primarily used by airline partners who are interested in updating information about their flights and gates.

By combining speech-to-text with BigQuery's analytics capabilities, you can understand things like customer sentiment and recurring product issues.