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.

Product quality is more important to the success of businesses than ever before. In a software market flooded with an ever-increasing pool of options, businesses and consumers alike demand high-quality, delightful experiences from the platforms and applications they use daily. In this market, getting QA right is essential. For the 2019 QA Health Survey, we polled over 250 software professionals to get a sense of how healthy quality organizations are right now.

Whether they connect existing on-premises applications to new cloud workloads, provide new customer experiences, or power an entire developer ecosystem, APIs are everywhere in today’s enterprise. And with more than two-thirds of enterprises adopting a multi-cloud strategy, APIs are increasingly distributed across private data centers and public clouds—sometimes even multiple public clouds.

Recently, I read why companies are failing in their efforts to become data-driven in the Harvard Business Review. It said that 72% of Chief Data Officers believe their organization doesn't have a data culture and 92.5% of them blame their people. But I think they’re wrong. The real issue is that people aren’t using the tools that their CDOs have bought for them. That means the problem isn’t with the users, it’s with the technology they’ve been given.

I recently had the pleasure of attending the Center for Business Analytics Career Panel event at Villanova University where myself and other analytics professionals sat on a panel to discuss the future of analytics with the students.