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?
Can we fix the plague in analytics with AI? Every Business Intelligence (BI) and analytics vendor is integrating a form of artificial intelligence (AI), machine learning algorithm (ML), and natural language generation (NLG) into their products. 'Augmented analytics', is the hot new topic and full of hype right now, but can it fix the fundamental flaw that has plagued BI tools for decades - adoption?
I often get asked why Yellowfin decided to go global. While the Australian market is relatively large, it’s also quite risk averse, which makes it a challenging market to sell into. While VC-backed software vendors have the benefit of selling to others within their VC family, as a bootstrapped startup we had to forge legitimate markets outside of Australia. We knew that we had to spread our wings to grow and expanding overseas quickly gave us the opportunity to sell faster.
