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AI success isn’t about algorithms—it’s about the data behind them. This month, we explore why strong data infrastructure and human support are critical, how most companies stall at the “integration plateau,” and why spreadsheets can no longer keep pace with modern analytics needs. We also dive into how AI and data fuel each other in next-gen architectures, and why reviewing AI data center policies is a must for security leaders. From smarter strategies to stronger safeguards,

From the precision of prescriptive analytics to the evolving capabilities of generative AI, organizations are racing to harness these advancements to create comprehensive data strategies. There are also tools such as customer data platforms that ensure valuable customer insights are unified and actionable. But it’s also important that the data strategy can be scaled effectively. And with the quantum future looming, leaders should be ready for the opportunities and challenges

From data interoperability and role-based masking in multi-cloud environments, to managing the complexity of AI systems and robust data governance powering self-service BI, organizations are reimagining how data is used at scale. We also highlight the transformative impact of real-time analytics in delivering immediate insights that fuel agility and competitive advantage.

We look deeper at the benefits of data in business innovation, as well as certain technologies such as data mesh for enterprise AI, continuous delivery for software and data deployments, and agentic AI in user interaction. We also explore one challenge facing businesses: the build-vs-buy tech debate in adopting technology...

Data isn't just changing how we work—it's redefining what's possible. Organizations that bridge the gap between information and insight are discovering opportunities hidden in plain sight. As analytics capabilities become more sophisticated and accessible, the real differentiator isn't who has the most data, but who asks the best questions of it. This shift is creating new possibilities across industries, from predictive customer experiences to supply chains that adapt in rea

There is always risk in adopting new technologies for the organization so it is crucial to minimize these risks by understanding the technologies to be deployed and that they are suited for the organization that will utilize them and, more importantly, practicing the right practices and fostering the proper mindset that will ensure the successful deployment of these new technologies...

Business operations continue to be transformed by new process improvements. Whether it’s Data Ops enhancing data analytics, data visualiza..

For data analytics to be effective in maximizing the value of your data, it is important to have the right analytics tools that can look...