Systems | Development | Analytics | API | Testing

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Shift Left: Headless Data Architecture, Part 1

The headless data architecture is an organic emergence of the separation of data storage, management, optimization, and access from the services that write, process, and query it. With this architecture, you can manage your data from a single logical location, including permissions, schema evolution, and table optimizations. And, to top it off, it makes regulatory compliance a lot simpler, because your data resides in one place, instead of being copied around to every processing engine that needs it.

Top 5 Tools For Performance Testing: Boost Your Application'S Speed

Performance testing t is a major part of software testing and involves understanding how the software handles expected errors, which is integral to quality assurance. There are multiple free and open-source tools we can discuss in the blog, but let’s start with why we even need performance testing.

The Impact of AI and Machine Learning In Quality Assurance

Some of the popular AI tools people and corporations are using now include ChatGPT, Google Gemini, and Microsoft Copilot. This has resulted in higher usage and adoption of this technology and this has caused some worry among people, particularly in terms of employment. However, for software testers, these changes should be seen as a chance to improve rather than a threat.

Informatica vs. Integrate.io: A Comprehensive Comparison for Data Integration

Table of Contents In this article, we’ll compare two popular data integration platforms—Informatica and Integrate.io. We’ll explore the key differences between them, focusing on usability, integration capabilities, pricing, scalability, and customer support. By the end, you’ll have a clear understanding of which platform best suits your business’s data integration needs.

Preventing Delays, Maximizing Efficiency: Real-Time Beacon Monitoring

In today’s fast-paced world, operational efficiency is paramount for businesses striving to stay competitive. The ability to manage time and resources effectively directly impacts overall performance. Our recent tech paper on – ‘Maximizing Efficiency by Real-Time Detection of Beacon Check-In Delays’, highlights how real-time detection technologies can revolutionize industries by identifying and mitigating inefficiencies caused by delays in beacon check-ins.

How Confluent Fuels Gen AI Chat Models with Real-Time Data

Discover how GEP, an AI-powered procurement company, utilized Confluent's data streaming platform to transform its generative AI capabilities. Integrating real-time data into their AI models enabled GEP to provide a contextual chat-based service. This chatbot allowed GEP customers to build their own tools simply by communicating in English with a chatbot.

Why Real-Time Data is Crucial to Developing Generative AI Models

Learn how GEP, an AI-powered supply chain and procurement company, harnesses real-time data streaming through Confluent Cloud to fuel its generative AI solutions. With seamless integration into Azure OpenAI services and GPT models, GEP’s generative AI chatbot delivers document summaries and risk management insights to its customers.

Building Reliable Software Systems with DoorDash's Saurabh Shanbhag

How do you ensure your software system is reliable from design to deployment? In this episode of Test Case Scenario, Jason Baum and Evelyn Coleman sit down with Saurabh Shanbhag, Software Engineer at DoorDash, to discuss the best approaches for preventing bugs and building reliable systems. Saurabh draws on his experience from Amazon, Uber, and DoorDash to explain how teams can focus on strong initial design, thorough testing, and smart monitoring to keep systems running smoothly.