When the Application Program Interface (API) first came into existence, developers viewed it as a revolutionary approach to creating re-usable software fragments. Instead of creating new code from scratch for every new program, they could now use existing functionality to develop new features. Not only did this decrease the amount of time needed to deploy a program but also meant they could leverage existing code which was already tried and tested.

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.

New customizable Home screen and improved design for quicker access to what’s important and a new wizard for building new dashboards faster.

We are in the era of the information economy. Now, more than ever, companies have the capabilities to optimize their process through the use of data and analytics. While there are endless possibilities to data analysis, there are still challenges with maintaining, integrating, cleaning it to ensure that it will empower the people to take decisions.

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 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.

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 neil.berns@allegro.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.

DevOps is all the rage right now, and it is only the beginning. In this blog, I’ll cover how to get started with Talend continuous integration, delivery and deployment (CI/CD) on Azure. The first part of the blog will briefly present some basic DevOps and CI/CD concepts. I will then show you how the Talend CI/CD architecture and how it fits in Azure ecosystem with a hands-on example.

Last month we brought together two data experts for a webinar discussion on best practices and approaches to implementing analytics and defining data roadmaps. The renowned Dan Vesset from IDC joined Qlik’s Michael Distler to review the current state of the data journey and how users can plan for success.