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?
In our recent poll on the health of the QA industry, we found that over half of all QA teams surveyed are not very confident in their ability to ensure a high-quality product. Having a high degree of confidence in your QA process is important, as it helps you ensure that every deployment goes smoothly and that resources are being allocated efficiently.
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.
