“According to BrowserStack, around 58% of companies are using visual testing in their QA cycle.” The need for creating high-performing web applications has pushed developers as well as QA teams to establish test methodologies that are ultra-productive. Be it test automation solutions or harnessing value through advanced test practices such as visual testing.

In the contemporary software development landscape, unit tests have become paramount for ensuring software quality. A prevalent practice during these tests involves mocking outgoing calls to decouple the code under test from external dependencies. Imagine, for a moment, a scenario where instead of writing mocks with pre-defined behaviours, you duplicate the behaviour of a real-world server.

Writing an effective bug report is essential for providing software developers with all the necessary information to understand, reproduce and resolve the issue. A well-documented bug report saves time and ensures a smoother debugging process. Writing a comprehensive bug report helps software developers quickly understand the issue and reduces back-and-forth communication. It's a key practice for effective bug tracking and issue resolution in software development.

Integrate YugabyteDB with BigQuery using CDC and why you would want to.

Like peanut butter and jelly, ETL and data modeling are a winning combo. Data modeling can't exist without ETL, and ETL can't exist with data modeling. Not if you want to model data properly. Combining the two defines the rules for data transformations and preps data for big data analytics. In the age of big data, businesses can learn more than ever about their customers, identify new product opportunities, and so on.

Data integration is essential for any competitive business. The ability to sync all your data from disparate sources powers better insights, analysis, and ultimately faster business decision-making. Change data capture (CDC) is one element of data integration that focuses on keeping data accurate with near real-time updates as soon as data within a data source changes.

Microsoft SQL is a popular relational database management system organizations use to manage and store data. As data volumes grow, extracting, transforming, and loading data has become essential for many businesses.

Amazon Simple Storage Service (Amazon S3) is a cloud-based object storage service from Amazon Web Services that collects data from anywhere on the internet. In today's data-driven world, businesses rely heavily on seamless data integration and transformation processes to unlock the full potential of their vast data resources. But what happens if you want to move data from Amazon S3 to a data warehouse for analysis?

Built with BigQuery, Live Ramp Safe Haven enables cross-channel marketing analytics to help customers execute media campaigns.

GenAI depends on data maturity, in which an organization demonstrates mastery over both integrating data – moving and transforming it – and governing its use.