Despite the transformative potential of AI, a large number of finance teams are hesitating, waiting for this emerging technology to mature before investing. According to a recent Gartner report, a staggering 61% of finance organizations haven’t yet adopted AI. Finance has always been considered risk averse, so it is perhaps unsurprising to see that AI adoption in finance significantly lags other departments.

"The whole is more than the sum of its parts." Aristotle is credited with this quote, and it's true in the world of data. Legacy systems typically approached their role in a limited manner. Each system was intended to be used by a certain user set and handle well-defined processes and associated data. The result was a disintegrated environment with data being difficult to obtain, and frequently out of date. The parts couldn't easily cooperate to make a whole.

When you’re ready to make the transition from manual testing to test automation, it’s natural to consider hiring. A QA engineer — who has the technical skills to write and maintain automated tests in an open-source framework — can take the burden of end-to-end test management off of your development team, allowing them to ship more code, faster. But hiring a good QA engineer is — often prohibitively — expensive.

The success of data warehouse solutions depends on how well organizations implement test cases to guarantee data integrity. As organizations evolve, data warehouse testing becomes crucial to adhere to industry best practices.

We've just rolled out new trigger controls and enhanced YAML syntax so you can initiate your builds with unmatched precision.

Enterprise Resource Planning (ERP) systems are designed to streamline business operations by centralizing data across an organization. However, extracting and utilizing this data can be a complex and time-consuming process. One solution to this problem is the use of APIs (Application Programming Interfaces), which allow you to get data out of ERP systems and other software applications.

At some point, anyone who has enjoyed using a computer has wondered if they could build their own app. But software development becomes intimidating fast if you’re not a programmer. Fortunately, there is a wide range of no-code platforms available today. Even in the enterprise, there’s demand for no-code development. As APIs have become one of the most important components of the modern application ecosystem, several no-code API solutions are now available.

In the age of digital transformation, enterprise continuous testing has become critical for agile and efficient software development. But enterprises often spend too much time managing a multitude of solutions and integrations with zero cohesion between solutions and an inability to gain clear insights. It takes so much time to manage the areas around testing that there is little time for the most important part — the testing itself.

Watch how to use a multimodal LLM such as Gemini to analyze data in a BigQuery data lake and automatically generate schema layouts.

Hey there! We're back for our third edition of Tips and Tricks. As we said in our first posts on Drizzle ORM and Template Databases in PostgreSQL, our new Tips and Tricks mini blog series is going to share some helpful insights and cool tech that we've stumbled upon while working on technical stuff. Today's topic is short and sweet. It'll be on CPU utilization and what that metric indicates. If you enjoy it and want to learn more, I encourage you to check out the "further reading" links.