Systems | Development | Analytics | API | Testing

Sam Altman, the key visionary behind the popular adaption of Gen AI and essentially the father of ChatGPT, deemed it “unthinkable” to have products and services without AI integration in the future. I’m sure that among other beliefs that inspired him to make such claims, the need for intelligence beyond efficiency in the modern digital ecosystem was a key one. It only makes sense to rethink IT management in this context and replace our traditional methods with the benefits of AIOps.

BigQuery external datasets for Spanner let you browse, explore and query Spanner tables as if they were native BigQuery tables.

Learn about an architecture built on BigQuery Omni that reduces the overall cost of log analytics by 10x as compared to a traditional approach.

It’s no secret that more and more organizations are turning to solutions that can provide benefits of real time data to become more personalized and customer-centric, as well as make better business decisions.

Every QA tester knows: time is money. When something breaks down on your website or web application, it can cause major issues for users within minutes. Because you’re constantly working to prevent fires from spreading (or happening at all), it’s important to have numerous strategies at the ready to help you manage your time wisely. One of these QA testing timesavers is called smoke testing. But exactly what is smoke testing?

Imagine getting into your car to head to work on a hot day. Your car already knows and sets the temperature, the ambient lighting, and the music you prefer. Not only that, it optimizes your route, and with Level 3 autonomy, it can even drive you there. But what does the automotive industry have to do on the backend in order to achieve this kind of personalization?

The dynamic landscape of product development continuously increases the scope of what is demanded from quality engineering (QE) professionals. So, it is not surprising that workplace learning and upskilling are critical to the organizational success, as highlighted by Workplace Learning Report: Without a doubt, the more technical side of the skill spectrum - e.g.

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

Complexity is increasing exponentially. Compared to just 20 years ago, our personal lives and the way organizations do business has changed completely. This translates into increasingly complex and interrelated business processes and a sprawl of IT systems that can only function when each of its components runs flawlessly. Navigating this business/IT complexity can only be overcome by combining business process solutions, quality assurance tools and human ingenuity and expertise.

Banking automation has become a key driver of efficiency and innovation in the financial services industry. As the banking sector strives to meet the demands of customers while managing costs, they’re turning to technology to streamline operations. But what exactly is banking automation, and how does it work? Let’s break it down. Banking automation refers to the use of technology by financial institutions to perform tasks that would traditionally require human intervention.