As generative AI continues to captivate attention with its transformative potential, there is a danger that traditional AI and ML become overshadowed. But as I mentioned in my last blog, this would be a mistake as traditional AI methods still hold immense value and relevance, and likely more so than generative AI in the near term.

A few weeks ago, I wrote a post summarizing "Seven Data Integration and Quality Scenarios for Qlik | Talend," but ever since, folks have asked if I could explain a little deeper. I'm always happy to oblige my reader (you know who you are), so let's start with the first scenario: Database-to-database Synchronization.

With any new, transformative technology comes a fear of the unknown, as I explored in my first blog of a new series on generative AI. Companies are pulled between acting quickly to avoid being left behind and proceeding with caution to avoid major missteps.

Five years ago, Qlik paved the way in powering our analytics platform with AI, with the introduction of natural language processing and generation. Our augmented analytics capabilities, which now also include fully interactive search, chat, and multi-language support, enabled a generative AI experience before it was cool. Today marks the next step in our AI journey with the launch of a new suite of OpenAI connectors to deliver a ChatGPT experience in Qlik Cloud.

Data fragmentation and the growing volume of data sources and types are putting increased focus and importance on an organization’s ability to continuously organize, transform and cost effectively deliver real-time data to its entire organization through the cloud.

Qlik and its NGO partners focus on leveraging data to bring a positive impact to the world. While we are still seeing the effects of the COVID pandemic throughout society, there are tremendous lessons that we can carry forward to be better prepared for the next likely pandemic.

The explosive rise of generative AI has prompted incredible excitement about its transformative potential, much like the advent of the Internet. But if like me, you’re old enough to remember what that looked like circa 1995, there was a lot we did not know at the time, creating uncertainty in both worlds of work and education on how to best leverage it, and whether providing unlimited access to employees or students was a good idea.

Last week’s announcement of a data fabric approach from Microsoft was interesting to us on a number of levels, most notably for what it confirmed: Data Fabrics are now mainstream. If you’ve not heard why Data Fabrics are the next big thing, then here is a bit of history. Data Fabric is a concept that started to take hold over a decade ago with published research from Forrester.

By now, you would have read the headlines that Qlik's acquisition of Talend is complete, and we're excited to expand our best-in-class capabilities to help you access, transform, trust, analyze, and take action with your data. You might have seen Mike Capone's QlikWorld keynote or the recent "What's Next is Now" webinar and wondered how to leverage these new capabilities in your organization.

For years data and analytics buyers have been managing a difficult set of tradeoffs. They know they need to invest in solutions to drive their businesses and data strategies forward. In fact, every third-party survey shows they plan to do so well into the future. However, customers have struggled in how to balance cost and value, and getting a clear answer isn’t always obvious or easy.