Systems | Development | Analytics | API | Testing

3 Key Pillars of Building a Culture of Quality in Engineering

Building a high-quality product takes teamwork. Maintaining a best-in-class product while continually developing high-quality features and giving a stellar customer experience, takes a quality-driven culture. We teamed up with Invotra in this new guide, Building a Culture of Quality: How Teams Can Use Quality to Achieve Business Goals, to explore the strategy behind building a culture of quality.

6 Strategy Elements for Building Cloud Native Applications

The cloud native paradigm for application development has come to consist of microservices architecture, containerized services, orchestration, and distributed management. Many companies are already on this journey, with varying degrees of success. To be successful in developing cloud native applications, it’s important to craft and implement the right strategy. Let’s examine a number of important elements that must be part of a viable cloud native development strategy.

Part 3: How machine learning, AI and automation could break the BI adoption barrier

In the first blog post of the series, we saw the dire state of analytics adoption. This problem feeds into the low usage and governance of data across organizations. Then, in the second post, we saw how the evolution of analytics has brought us to a prime position for augmented analytics. But will this new wave of augmented analytics break through the barriers to BI adoption?

The Embedded Vision Summit in Santa Clara to Feature a Talk by allegro.ai's Chief Technology Officer

This conference is shaping up to be the largest ever focused on Computer Vision and Visual Artificial Intelligence. We invite you to attend the session and meet our experts. To arrange a time to meet during the conference, send an email to Neil Berns at [email protected].

How to accelerate your path to AI

Software vendors that are looking to accelerate their path to AI need to take advantage of the AI already in analytics platforms. Gartner believes that the future of analytics is augmented. That is, analytics will be AI-driven and all end-to-end use cases will be automated. I also believe it won’t be long before analytics is no longer on our desktops - instead it’ll be embedded in applications.

Part 2: How machine learning, AI and automation could break the BI adoption barrier

If, as we saw in part one of this series, 77% of businesses are 'definitely not' or 'probably not' using analytics to its full extent and the adoption rate of analytics platforms is an abysmal 32%, something drastic needs to happen. Can the era of augmented analytics with its machine learning and AI fix this adoption issue?