The success of your mobile app depends not just on how well the application is working at first, but also on its consistent delivery of excellent user experience. Customers today have an extensive range of alternatives in this rapidly evolving & competitive mobile market. Any problem with the application's performance and user experience can lead to users being discontent with the mobile app. This results in users abandoning the application.

There's no doubt that, as a technology provider/integrator, you're likely seeing many customers across all segments looking to advanced analytics and artificial intelligence for optimizing their growth. Given the vast volume of data that these innovations consume or create, it's clear to see the importance of being able to offer your customers reliable, secure, sustainable and scalable data infrastructure solutions.

In the video game development industry, releasing a well-polished and critically acclaimed title is crucial to success. However, even experienced development teams may face unexpected challenges in identifying and resolving issues before the official release. This is why beta testing is so important; it helps developers catch and fix any remaining problems before the game is released to the public.

In this blog post we are going to look at how we can use our performance tests to act as Sanity Test. We have touched upon the subject in one of our blog posts on the hidden benefits or performance testing. This post will however look to provide more detail on the subject and provide guidance on how you can accomplish this. We are not suggesting that you write a set of JMeter tests to act as sanity tests for our application under test as that would not be that beneficial.

Companies are moving to the cloud faster than ever. Currently, organizations deploy an average of 130 SaaS apps per organization — and this number is growing. According to Gartner, 95% of new apps are expected to be built in the cloud by 2025.

IT leaders who want to scale operations to meet future business needs face an epic challenge—improving operational efficiency while managing risk, ever-growing IT backlogs, and stakeholder expectations. That's where process orchestration comes into play. Process orchestration is not just about efficiency and scale. It's a transformative approach that revolutionizes how work gets done. By automating routine tasks, it frees up your workforce to focus on strategic initiatives.

It's hardly groundbreaking to mention the importance of data privacy in the digital world and in business…it's a topic we've previously explored. However, acknowledging its significance is one thing, implementing actionable steps is another. This realization is the inspiration behind this article. There’s no need for you to jot anything down or replicate the checklist, as we’ve prepared a downloadable gated version ready at the conclusion of this article. So let’s get into it.

Like many tech endeavors, QA has undergone radical evolution over the past decade, and to keep up with the competition, dev teams are looking toward the future of QA and test automation. Since machines can do low-skill testing, dev teams are looking for expertise and complex skill sets, which means that human testers’ day-to-day responsibilities are changing thanks to automation. In this article, we will discuss test automation, what it is, examples, types of test automation, and uses.

Learn how to use BigQuery’s new CDC capability in Dataflow and its at-least-once streaming mode to simplify your CDC pipeline and reduce costs.

In the last couple of years, AI has launched itself to the forefront of technology initiatives across industries. In fact, Gartner predicts the AI software market will grow from $124 billion in 2022 to $297 billion in 2027. As a data platform company, Cloudera has two very clear priorities. First, we need to help customers get AI models based on trusted data into production faster than ever.