API (application programming interface) testing is a type of software testing that performs verification directly at the API level. It is a part of integration testing that determines whether the APIs meet the testers’ expectations of functionality, reliability, performance, and security. Unlike UI testing, API testing is performed at the message layer without GUI.
As more and more businesses look to the cloud to store and manage their data, an increasing number are embracing BigQuery as their serverless, highly scalable, enterprise data warehouse.
This is the second part of my blog series on CI/CD best practices. For those of you who are new to this blog, please refer to Part 1 of the same series and for those who want to see the first 10 best practices. Also, I want to give a big thank you for all the support and feedback! In my last blog, we saw the first ten best practices when working with Continuous integration. In this blog, I want to touch on some more best practices. So, with that, let’s jump right in!
We polled dozens of agencies to find out which project management tools they use and how they use them to build successful project management processes.
A few weeks ago we brought you a rundown of our five favourite automation testing tools for Android, and the response was overwhelming. So we’ve written a follow-up article, this time for iOS developers. The testing challenges vary slightly for Android and iOS testing. For one thing there are far more Android models out there than iOS, which means lots more potential bugs. Also, the two variants have their own default languages, which further complicates things.
With millions of downloads, Talend Open Studio is the leading open source data integration solution. Talend makes it easy to design and deploy integration jobs quickly with graphical tools, native code generation, and hundreds of pre-built components and connectors.
Ecommerce is changing all the time — and so is ecommerce SEO.
Track all of your critical subscription metrics in Databox from a free ProfitWell account: revenue, churn, upgrades/downgrades, ARPU, and much more.
The next generation of BI will heavily integrate machine intelligence and AI – and how these technologies are embedded and used will matter. The best solutions will support human-centered analysis, which takes advantage of new technology while not losing sight of value of the human perspective in decision making and analysis.
One of the best things about my job is that I get to continually scan the industry and learn about who’s driving innovation (see my predictions for 2018 here). As a result, I see five key trends emerging in the analytics space over the next year.
