When a data breach occurs, your response is critical. What do you do first? Do you have a plan for communicating with business units, regulators and other concerned parties? The integrity and security of data infrastructure stand as paramount concerns for business leaders across all sectors. As technology evolves and threats become more sophisticated, the pursuit of an unbreakable data infrastructure remains an ongoing challenge.

In this age of data dominance, data democratization becomes a lifeline for any organization trying to harness the most out of its information-based assets. Data democratization ensures access to data for all employees across varying organizational departments without technological barriers, which enables data-based business decisions to be made. Empowering the team members with the approach will open doors for improved collaboration and innovation.

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.

To execute locally, remote, or on-cloud? That is the question. But test execution is more than just “hitting Enter and seeing if it passed or not.” If you are doing it manually, test execution is about performing every single test step as outlined in the test case. For automation testing, test execution takes on another layer of complexity: In which environment should you run the test? Which test cases should you prioritize for execution?

Any (functioning) system is built upon an infrastructure. This infrastructure supports all of the functions and activities of the system. Testing is no exception. With a good test infrastructure, QA teams can speed up their testing efforts and drastically improve efficiency. In this article, we will explore the concept of test infrastructure, and how you can effectively build one.

For enterprises, commercial use of AI is still in its early stages, and it’s a case of risk and reward, weighing up both and investigating the best way forward. Of course, there’s much to gain from the use of AI. Already, companies are providing better customer service, parsing complex information through natural language inputs, and generally making workflows faster.

Generative AI (GenAI) has taken the world by storm, promising to revolutionize industries and transform the way businesses operate. From generating creative content to automating complex tasks, the potential applications of GenAI are vast and exciting. However, implementing GenAI in an enterprise setting comes with its own set of challenges. At Cloudera, we understand the complexities of enterprise GenAI adoption.

HubSpot, Snowflake and Fivetran marketing executives discuss how a modern data stack enables enterprises to meet customer expectations and drive results.

At the end of every testing project, a test report is usually created to summarize the results. This report provides insights into how the test project was executed if it aligned with the initial plan, and what areas need further optimization. In this article, we’ll explore in-depth what needs to be included in a test report, as well as the key metrics that QA teams need to look at if they want to gauge their testing efficiency.