Systems | Development | Analytics | API | Testing

Part 4: How machine learning, AI and automation could break the BI adoption barrier

In the last three parts of this four-part series, we have looked at: research on the state of analytics today and the lack of BI adoption; the history of BI and how we have arrived at the augmented era; and the four main blockers to BI adoption that is stunting the growth your business data culture. Today, let's take a look at how AI and machine learning (ML) can close that adoption gap.

The Qlik Sense April 2019 Release

April is an exciting time at Qlik as we build momentum towards Qonnections 2019 and later in the quarter, the global Qlik Analytics Tour. These great events will showcase Qlik Sense April 2019 – which is now available! This release sets us apart from the competition with significant advancements to our multi-cloud capabilities – including a new enterprise SaaS deployment option, as well as innovative advancements to our market leading AI capabilities.

Delivering Connected Customer Experiences with APIs

Today’s connected experiences — such as controlling smart home accessories from a mobile app or ordering takeout via a voice assistant — involve a lot of software talking to other software. This means these digital experiences rely in large part on application programming interfaces (APIs). When someone uses their social media account to log into other websites, an API mediates the interaction.

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?