Started in 2009 as a research project at UC Berkeley, Apache Spark transformed how data scientists and engineers work with large data sets, empowering countless organizations to accelerate time-to-value for their analytics activities. Apache Spark is now the most popular engine for distributed data processing at scale, with thousands of companies (including 80% of the Fortune 500) using Spark to support their big data analytics initiatives.

According to the World Health Organization (WHO), Up to 50% of medical errors in primary care stem from administrative issues. There is a projected shortfall of 10 million health workers by 2030. Given the statistics highlighting device errors and a shortage of maintenance professionals exacerbate healthcare challenges, Generative AI in medical devices offers diversified solutions.

A balanced combination of manual and automated testing is the way to go if you want to achieve higher test coverage and efficiency. They cover for each other. Manual testing is easy to learn and do, but it is highly likely to create inconsistent test results, and sometimes it takes a lot of time and effort. On the other hand, automation testing requires a lot of technical expertise to create and maintain scripts, but it checks bugs much faster with higher consistency.

In the last article, we gave a general introduction to using Swift for backend development. We discussed its advantages: its robustness, stability and, above all, its simplicity. Now we’re going to drill a little deeper, and provide some best practices that will help you in your day-to-day work. Our work today will focus on Vapor, an open-source web framework that provides a robust foundation for websites, APIs and Cloud projects.

Here’s a look at how we scored and our key takeaways from the report We're thrilled to be recognized as a Leader in The Forrester WaveTM: API Management Software, Q3 2024! We believe this recognition validates our commitment to empowering businesses with the tools they need to unlock the full potential of their APIs.

Modern applications store a lot of data, yet databases continue to be the primary source of data that these applications need to function. This is where database APIs come in, making it easier for applications and services to retrieve and manipulate data. A database API’s biggest advantage is that it eliminates database operations’ dependence on proprietary methods and provides a unified interface, streamlining data operations. Here’s everything you need to know about database APIs.

Spring Boot is an open source Java framework designed to facilitate the creation of stand-alone, production-grade Spring applications. Whether you’re developing a RESTful API, a microservice, or a batch task, Spring Boot simplifies the process. While platforms like Microsoft Azure and Amazon Web Services (AWS) offer cloud deployment options for Spring Boot applications, Choreo provides specialized features and tools tailored specifically for Spring Boot, streamlining deployment and management.

Learn about BigQuery data canvas in this technical walkthrough with a real-world example based on the public github_repos dataset.

An API allows communication between different systems, and like any other software, it requires clear instructions so developers can use them effectively. Clear and comprehensive API documentation helps developers understand how to use APIs in their applications. API documentation tools simplify creating detailed reference docs, tutorials, and API documentation. These tools assist in documenting REST, SOAP, or GraphQL APIs effectively. They produce comprehensive API docs that support developers.

Tips for writing natural language prompts to generate SQL and charts using BigQuery data canvas’ NL2SQL and NL2Chart capabilities.