Systems | Development | Analytics | API | Testing

Qlik Joins Snowflake-Led Open Semantic Interchange to Bring Consistent Business Meaning to Analytics and AI

If you have ever asked three teams for the definition of the “same” metric and gotten three different answers, you have already met one of the most expensive, least talked about problems in modern data. It is not a lack of data. It is a lack of shared meaning. As analytics and AI spread across more tools, clouds, and teams, business context often fails to travel with the data. A metric defined one way in a dashboard gets redefined in a notebook.

Chat with Your Data: The Official Databox MCP

Your AI is brilliant, but it’s blind. Until now. We are thrilled to launch the official Databox MCP (Model Context Protocol). This open standard server bridges the gap between your business data and your favorite AI tools, turning general-purpose LLMs into specialized data analysts that know your business data. Stop manually exporting CSVs or taking screenshots of dashboards. With Databox MCP, you can connect 130+ data sources (Google Analytics, HubSpot, Salesforce, Stripe, and more) directly to tools like Claude, ChatGPT, Cursor, and n8n.

Top 5 BrowserStack Alternatives in 2026

BrowserStack is a popular web and mobile testing platform, but in 2026 many teams are actively searching for BrowserStack alternatives to simplify testing, lower costs, and automate at scale more efficiently. But how do you pick the right BrowserStack alternative testing tool? Do you rely on user reviews, popularity, or the most budget-friendly option?

AI-Powered Loan Management Software Development

The world has really come a long way due to widespread digital transformation adoption! And, it’s no secret that it has changed the FinTech sector drastically. In light of this evolution, it has become imperative for lenders to adapt and refine their operations with a well-defined Loan Management System.

Code coverage vs. test coverage in Python

If you have been writing tests for a while, you have probably encountered code coverage and test coverage. These concepts can be difficult to differentiate because they are somewhat intertwined. In this article, you will learn what code coverage vs test coverage means, and the basis of these concepts. You will also learn the key differences between code coverage and test coverage in Python. You would discover tools, techniques, and best practices to improve your testing strategy.

Escaping the Integration Tax: Why Your Partners Are Stuck in Limbo (and How to Onboard in Days, Not Months)

In a high-interest-rate environment, the most expensive asset a bank can hold is a signed partner contract that isn’t generating transaction revenue. For many regional banks, the 4–6 month gap between “contract signed” and “first transaction” is driven by manual compliance reviews, fragmented security processes, and custom integration work that delays go-live. We call this the “Integration Tax.”

How to build a Copilot agent

A customer recently shared their debugging workflow with me. When an error shows up in Honeybadger, they import it to Linear, manually add context about where to look in the codebase, then assign GitHub Copilot to investigate. It works, but they asked a good question: could Copilot just access Honeybadger directly? The answer is yes—and it's easier than I expected.