Systems | Development | Analytics | API | Testing

Keboola to Simplify the Management of Sustainability Data

Keboola, the self-service data management platform, develops a comprehensive platform that simplifies Environmental, Social and Governance (ESG) data management. It automates data collection, monitors key performance indicators (KPIs), and provides real-time insights across all client entities. By replacing manual processes, it ensures precision, uniformity, and adherence to ever-changing regulations.

Mastering ETL Data Pipelines with Integrate.io

In the fast-evolving world of data analytics and data models/machine learning applications, the power of a well-structured ETL (Extract, Transform, Load) pipeline cannot be overstated. Data analysts in mid-market companies often grapple with transforming large data sets from disparate data sources into actionable insights. Here’s where ETL platforms like Integrate.io emerge as the unsung heroes, simplifying complexities with low-code and scalable solutions.

Comparing Github Copilot Vs. Chatgpt For Unit Testing

With the rise of AI-driven tools, the debate of ‘ChatGPT vs Copilot’ has become central for developers seeking productivity boosts in coding and testing. In this blog, we will dive into the key features, strengths, limitations, and use cases of these tools to help you understand their differences and make an informed decision on which one suits your programming needs the most. So, let’s get started!

9 Test Automation Best Practices to Start 2025 Off Right

As we round the bend into 2025, here’s our best advice for maximizing your automation testing productivity and avoiding mistakes. Automated testing entails much more than simply creating tests and enabling them. A “set it and forget it” approach won’t get you very far with automated tests — particularly automated browser tests, which interact with the ever-changing frontend of your application or website.

Testing Kubernetes Ingress with Production Traffic

Kubernetes is an incredibly powerful solution, but testing the Kubernetes Ingress resources themselves can prove to be quite tricky. This can lead to significant frustration for developers – bugs can pop up in production that weren’t caught during testing, workflows that make sense on paper might fail in practice, and so forth.