Today’s data-driven world requires an agile approach. Modern data teams are constantly under pressure to deliver innovative solutions faster than ever before. Fragmented tooling across data engineering, application development and AI/ML development creates a significant bottleneck, hindering the speed of value delivery required to stay competitive. Disparate tools create a complex landscape for developers and data teams, hindering efficient pipeline development and deployment.

Discovering and surfacing telemetry traditionally can be a tedious and challenging process, especially when it comes to pinpointing specific issues for debugging. However, as applications and pipelines grow in complexity, understanding what’s happening beneath the surface becomes increasingly crucial. A lack of visibility hinders the development and maintenance of high-quality applications and pipelines, ultimately impacting customer experience.

In the dynamic world of software development, quality is paramount. Every line of code, every feature, every functionality needs to be meticulously evaluated to ensure a flawless user experience. This is where test cases come in – the unsung heroes of the development process.

Why should you prioritize an API design-first approach in your development strategy? This essential methodology promotes early and thorough API specification, fostering a blueprint that guides the entire development process. You can cut straight to improved efficiency, consistency, and quality in your API projects by embracing this approach from the start.

As a developer, you usually work with JSON data, and may need to compare JSON files. This might involve checking a list of products from the database against a previous version or comparing an updated user profile returned by your REST API with the original data sent to the server. In this article, we’ll explore several methods and tools developers can use to compare two JSON files effectively.

How to use Gemini generative AI models through BigQuery to boost productivity in Google productivity tools like Sheets.

You've likely heard the term webhook at some point. But what are webhooks? Five key takeaways from What Are Webhooks.

In today's rapidly evolving digital landscape, superior software is essential, whether it be the apps on our phones or the intricate systems supporting various business requirements. The process known as Software Testing (ST) has undergone an immense transformation in order to meet this necessity where Artificial intelligence (AI) and machine learning (ML) play a great role in QA solutions.

The BigQuery ML.GENERATE_TEXT function lets you use LLMs from Vertex AI within your SQL queries to analyze text in a BigQuery table.

While quality assurance (QA) and quality control (QC) are often used interchangeably, they are distinct processes that work together to ensure your software quality meets customer expectations. This article will cover the key similarities and differences between QA and QC.