Since AccuWeather was founded in 1962, our company has become the world’s leading provider of weather forecasts and warnings. We maintain a huge, accurate and comprehensive collection of weather warning data. Back then, we brought data to local forecasts, newspapers, radio stations and small businesses. While we started by putting pen to paper and providing solutions to business customers, AccuWeather has really evolved into a digital platform over the past decade.

You may have noticed a few new (and colorful!) elements in your Rainforest run results lately. In this post, let’s walk through how the changes to your test results will help you have a cleaner, easier run review and bug triage experience in Rainforest.

The Ghost Inspector team got together for our annual company off-site in Austin, TX this year. We always plan our off-site around presenting at an industry-related event. This year we were thrilled to present to the Austin Automation Professionals Meetup on the topic of headless browsers and testing at scale.

We know that data is a key driver of success in today data-driven world. Often, companies struggle to efficiently integrate and process enterprise data for fast and reliable analytics, due to reliance on legacy ETL solutions and data silos. To solve this problem, companies are adopting cloud platforms like Microsoft Azure to modernize their IT infrastructure.

Last year, Yellowfin changed the world of business intelligence and analytics with the introduction of Yellowfin Signals. We automated data analysis, removed dashboard dependency, and sped up the process where you would get alerted to the most important changes in your business data, just ask AeroEdge.

A common perspective that I see amongst software designers and developers is that Machine Learning and Artificial Intelligence (AI) are technologies which are only meant for an elite group. However, if a particular technology is to truly succeed and scale, it should be friendly with the common man (in this case a normal software developer).

Azure SQL Data Warehouse (DW) has quickly become one of the most important elements of the Azure Data Services landscape. Customers are flocking to Azure SQL DW to take advantage of its rich functionality, broad availability and ease-of-use. As a result, Talend’s world-class capabilities in data integration, data quality and preparation, and data governance are a natural fit with Azure SQL DW.

KissFront is a web performance monitoring tool running Lighthouse continuously or on-demand (using Lighthouse as a service) to monitor your website performance and get insights on speed with modern performance metrics. Lighthouse is an open-source automated tool for analysing and improving the quality of web pages with audits for performance, accessibility, progressive web apps, SEO and best practices.

Since the release of Talend 7.1 users can build Talend jobs as Docker images and publish them to Docker registries. In this blog post, I am going to run through the steps to publish to the major cloud provider container registries (AWS, Azure and Google Cloud). Before I dig into publishing container images to registries, I am going to remind you the basics of building Talend Jobs in Docker images from Talend Studio as well as point out the difference between a local build and a remote build.

In Yellowfin 8 we introduced two new products, Yellowfin Signals, to automatically discover the most critical changes in your business as they happen, and Yellowfin Stories, to provide context to the numbers and tell compelling stories with your data. We’ve received great feedback since then and implemented some of the requested enhancements to improve the user experience, increase governance and performance.