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From artificial intelligence (AI) to machine learning (ML) to conversational chatbots, the tools we use to interact with and consume information are rapidly changing thanks to powerful new technologies that make understanding our data more accessible than ever. One particularly influential field is natural language technology (NLT) and its branches.
As we transition into the next era of information technology, organizations face increasing pressure to deliver value to customers more rapidly. As well as higher quality, flexible access to data and applications and uncompromised security. Concurrently, they must manage growing complexity, including increasingly distributed hybrid cloud architectures and data sprawl – and accompanying costs – in order to remain competitive.
Being able to create and share insightful data-led stories to support your dashboards and reports is a critical capability in today’s modern workplace. You want your data to be accessible for more people, and ensure everyone gets value from your investments. Data storytelling tools bring valuable context to the ‘why’ behind the results, while inspiring your audience to care about and act on insights.
In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI. One of the most important innovations in data management is open table formats, specifically Apache Iceberg, which fundamentally transforms the way data teams manage operational metadata in the data lake.
Qlik Anonymous Access is an exclusive, new capability that enables organizations to share analytics insights with a public audience easily. It leverages Qlik Cloud’s secure and scalable platform, allowing you to embed Qlik Sense apps, dashboards, and visualizations into websites or third-party applications using shareable links or our new Qlik Embed APIs. With Anonymous Access, no login credentials are required, simplifying engagement with embedded analytics.
In recent years, machine learning operations (MLOps) have become the standard practice for developing, deploying, and managing machine learning models. MLOps standardizes processes and workflows for faster, scalable, and risk-free model deployment, centralizing model management, automating CI/CD for deployment, providing continuous monitoring, and ensuring governance and release best practices.
In this episode of the "Data Cloud Podcast", Bill Stratton, Global Head of Media, Entertainment & Advertising at Snowflake, sits down with Ravi Kandikonda, Sr. VP of Marketing at Zillow. Ravi shares his experiences and insights on modern software development, talks about how his academic background prepared him for modern marketing, and what Zillow is doing to approach personalization at scale.
Unravel Data is the DataOps observability platform for the modern data stack. Unravel provides AI-powered recommendations for performance, cost governance, and quality so data teams spend less time firefighting and more time innovating. Let’s see how it works.