Discover our latest thinking on the topics that matter most in business, data, and technology.
Our strategic actions start with intuitive understanding
As companies grapple with the opportunities and challenges of AI, the role of data governance is more important than ever.
Data quality is key to operational efficiency, speed to insight, AI enablement, and other high-value analytics.
Implementing an AI Data Analytics solution can bring additional efficiency and insight if you start by building these foundational components
To get the most value from your AI implementation, it's critical to ensure your data initiatives are aligned with your AI solution's requirements.
Is it possible to maintain data privacy while bringing improved personalization to healthcare marketing? Yes, with an enterprise data strategy enabled by API principles and an integration focus.
The best way to assure success along your data journey is to align on a Data and Analytics Strategy first.
Data fabrics represent the next evolution of data architecture as they provide flexibility, scalability, and efficiency, yet they remain an enigma to many.
What if there was an easier way to harness data from emails, reports, and other written documents? Enter Generative AI.
Just as with all technologies, getting the most out of artificial intelligence requires a comprehensive data strategy.
Learn how the new Generative AI technology can be put to use in a contact center.
Master data management is key as the amount of data companies are acquiring is expanding rapidly. Building an MDM program sets you up for success now and in the future.
Building a data-driven culture into your product management processes is key to setting your team up for success.
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