Systems | Development | Analytics | API | Testing

We decided to pursue a regional growth strategy quite early on. As an Australian company, we believed it was necessary to look overseas to grow our business quicker. We knew it wasn’t going to be easy, but there were three important lessons that we didn’t expect to learn when we set out overseas.

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?

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.

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?

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.

Is it the Data Scientists and Millennials, or should our minds be broadened to look for other groups in our organisations that need and want data and it’s insight?