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Jon Alexander
AI Isn’t Static. Why Are We Still Feeding It Yesterday’s Data?
The AI tools dominating today’s headlines are dazzling but misunderstood. We've confused model training for genuine…
Salvatore Salamone
How AI Enhances Predictive Analytics
In a landscape defined by rapid digital transformation, AI-powered predictive analytics is becoming a strategic capability…
Udaya Veeramreddygari
AI-First Development: The Strategic Imperative for Modern Enterprises
The digital landscape has reached a pivotal moment where artificial intelligence is no longer a competitive…
Joe McKendrick
Are We Ready for the Real-time Demands of AI? Survey Says No
Are organizations ready for the need for real-time observability and intervention in their rapidly emerging AI…
Why DataOps Is Critical to Successfully Scaling AI
AI projects often fail to scale due to poor data quality and siloed pipelines. Learn how DataOps provides the governance, automation, and real-time capabilities needed to deliver reliable AI at enterprise scale.
A Framework for Taking AI Pilots from Experiment to Enterprise
This framework provides phased validation, continuous integration, and comprehensive risk management, empowering firms to transition from pilot to enterprise use with resilience and assurance.
Bad Data = Missed Revenue: Why GTM Success Starts with Clean Data and Execution-First Intelligence
Companies that invest in structuring their first-party data today are laying the groundwork for AI systems that don't just guide work; they do it.
AI Isn’t Static. Why Are We Still Feeding It Yesterday’s Data?
Developers need large context windows for breadth, automatic caching for efficiency, and easy-to-use embedding pipelines for retrieval.
AI Prompts are Real-Time Energy Pits
To address concerns about energy consumption, AI system providers are using research innovations and software and hardware improvements to increase energy efficiency.
Real-time Analytics News for the Week Ending September 20
In this week's real-time analytics news: NVIDIA and Intel Corporation announced a collaboration to jointly develop custom data center and PC products to accelerate applications and workloads.
Rethinking DevOps: What’s Next for Software Teams After a Decade of Stagnation
It’s time to redefine DevOps, not as a set of tools or rigid methodologies, but as a human-centered, technology-enabled movement towards shared accountability and better software delivery.
Turning Unstructured Data into a Manageable Enterprise Asset
For data analysts, engineers, and scientists, automation can support AI and machine learning initiatives by giving them increased control, reduced overhead, and a clear, policy-driven approach to managing unstructured data at scale.
The Revenue AI Imperative: Connecting Data, Context, and Guided Selling in Real Time
For enterprise revenue AI to work, it needs more than data. It needs context. Without it, accuracy breaks, decisions stall, and trust disappears. Here’s how to fix that.
How AI Enhances Predictive Analytics
Companies moving to AI-powered predictive analytics are reporting measurable gains and leading firms are documenting robust ROI.
Turning Data into Action: Why AI-Driven Business Intelligence Still Fails – and How to Fix It
Getting real value from AI-driven BI isn’t just a matter of tools or training. It requires a cultural shift toward accountability, cross-functional collaboration, and continuous learning.
AI Readiness is the Real Race – So Why Aren’t Organizations Set Up to Win?
As more organizations race to showcase AI capabilities, it’s easy to feel pressure to move fast. But AI readiness isn’t about speed. It’s about building a foundation that lasts.
How Kafka and Edge Processing Enable Real-Time Decisions
By pairing Kafka with adaptive edge processing, organizations achieve the best of both worlds: instantaneous local decisions and enterprise-wide intelligence.
Real-Time Decisions at the Edge: Adaptive Edge Intelligence Use Cases Across Industries
Discover how adaptive edge intelligence drives real-time fraud detection, network optimization, predictive maintenance, and anomaly detection across industries.
Real-time Analytics News for the Week Ending September 13
In this week's real-time analytics news: MLCommons announced new results for its industry-standard MLPerf Inference v5.1 benchmark suite.
The Expert Agent Imperative: Why Specialized Intelligence Will Define Enterprise Success
The question facing every enterprise technology company is simple but urgent: Will you be an essential expert agent that first agents rely on, or will you become a legacy system that agents occasionally query?
Why Interoperability Is the Next Big Test for Enterprise AI Agents
Interoperability is critical because AI agents have to be able to share tools, context, and tasks securely across boundaries.
Why Data Quality Is the Cornerstone of AI Success
In today’s AI-driven business environment, data quality is essential to ensure smarter decision-making, lower risk, and more agile responses across the enterprise.
Navigating the Evolution of AI: Trust, Oversight, and the Power of Agentic Systems
For enterprises to harness the full potential of agentic AI, they must invest in planning, robust training, and continuous learning.
The Changing Landscape of Telcos: 6 Trends That are Shaping the Future
Telcos will rely heavily on artificial intelligence and AI agents to meet user demands, increase operational efficiencies, carry more traffic, and improve services.
Sovereign By Design: Own the Data, Own the Outcome with Strategic Object Storage
Sovereign AI demands that data must not “disappear” into opaque, unmanaged cloud platforms or third-party silos.
AI-First Development: The Strategic Imperative for Modern Enterprises
AI-First Development has evolved from an innovative approach to a strategic necessity for enterprises seeking to remain competitive in today's rapidly changing business environment. Organizations that embrace this methodology position themselves to deliver superior customer experiences, achieve operational excellence, and respond effectively to market dynamics.
Studies Find Scaling Enterprise AI Proves Challenging
To successfully scale enterprise AI, organizations must focus on enterprise productivity, rather than just individual task augmentation.
Addressing the Hidden Security Risks of AI Agents in Industrial Operations
Industrial organization using AI agents must treat them as first-class citizens in the security architecture, not just as tools.
Real-time Analytics News for the Week Ending September 6
In this week's real-time analytics news: Siemens and Snowflake announced a collaboration to connect OT and IT data.