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.

Just be honest, when you were 12 years old, did you ever imagine that your life would be this much digitalized by 2024? If you take your memories a decade back, wouldn’t it be difficult for you to think about how technology will be so infused into your lives in the coming years? Well, as you know every industry has been now digitalized directly or indirectly and the Automotive industry is no exception.

Software testing can feel like you're walking a tightrope—striving to uphold impeccable quality standards while the clock ticks towards your next release. It’s a daunting challenge to make sure every test is planned and executed with speed, all while hoping there are no blind spots in your process. Enter test management. It’s a great way to ensure your tests remain organized, efficient, and consistent. And of course, so you can report on this hard work to leadership.

As generative AI grows in popularity and enterprises scramble to embrace new technology in a scalable, compliant way, it can be difficult to know the right path forward. Your enterprise has already invested in automating processes to free up resources and improve organizational efficiency, but is it enough? This is where intelligent process automation comes into play.

You open your Uber app and book a ride. Upon successful booking, a map pops up and shows you the whereabouts of your driver. While in the Uber, you open Zillow, a real estate app, to check out the apartment you want to rent that is located a few kilometers away from your location. The weather app, knowing your location, then sends you a notification to expect rain tomorrow. All of these are examples of the power of geolocation-based app features.

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems.

Download a sample report that includes insights into the health of a Snowflake data estate.

In this post we are going to look at performance test coverage. What functionality to performance test can range from very little to most of the application under test and both are valid under the right circumstances.

You’re searching for “Selenium alternatives” because, while Selenium is a popular open-source test automation tool, it has certain limitations. Its slow execution speed can be problematic when dealing with large test suites or complex applications. The basic reporting and analytics features make finding problems and testing results difficult. It also lacks a mobile app testing focus — an essential feature for most organizations.

This guest blog highlights how our strategic partnership with General Catalyst has fueled Fivetran's growth, showcasing our journey towards scaling innovation and efficiency.