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Modern data platforms are evolving—and speed, scale, and efficiency are becoming non‑negotiable.

In this episode of Exchanges with Hitachi Solutions, host Matt Volke sits down with Evan Sotos, Engineering Manager for the Empower Data Platform, fresh off his return from NVIDIA GTC. Together, they explore how GPU acceleration is moving beyond AI and machine learning—and into the core of data engineering.

The conversation dives into what Evan heard from engineers, partners, and vendors at GTC, why NVIDIA is positioning itself as an algorithms company, and how technologies like NVIDIA RAPIDS are being used to dramatically accelerate analytics and data pipelines without rewriting existing code.

What You’ll Learn

· Why GPU acceleration is becoming a core capability for modern data platforms, not just AI workloads

· What NVIDIA RAPIDS is and how it enables existing CPU‑based workloads to run on GPUs

· How GPU acceleration can significantly reduce processing time and overall compute costs

· Why “zero code changes” is such a critical advantage for real‑world data teams

· Which types of data workloads benefit most from GPU‑accelerated pipelines

From AI Buzz to Real‑World Data Engineering Impact

While NVIDIA GTC is often associated with AI and large language models, this conversation highlights a broader shift: GPUs are increasingly being applied to traditional data engineering and analytics workloads.

Evan shares how NVIDIA RAPIDS acts as a mapping layer that allows existing Spark and Databricks workloads to take advantage of GPU compute. Rather than forcing teams to refactor complex, production‑grade code, GPU acceleration can be enabled through configuration—making it practical for teams to test, validate, and adopt without disruption.

The result? Faster pipelines, improved cost efficiency, and a shorter path from raw data to actionable insight—especially for large, time‑sensitive workloads.

What This Means for Data Teams

For organizations running large‑scale analytics, predictive models, or operational reporting, time truly is money. Evan explains how accelerating data pipelines can directly impact downstream use cases—from predictive maintenance to real‑time decision‑making—by reducing the lag between data ingestion and insight.

Most importantly, this episode emphasizes practicality: GPU acceleration isn’t about chasing hype. It’s about giving data teams another tool they can turn on, test, and adopt when it makes sense—without introducing risk, rework, or operational complexity.

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The Future of Field Service: From Cost Control to Value Creation

Field service is evolving—and value is the new metric that matters.

In this episode, Ginny Lebeck, Michael Mendoza, and Boris Klimovitsky break down the biggest shifts shaping modern field service, from AI adoption to revenue‑driven transformation. Learn why leading organizations are moving beyond technology for technology’s sake and focusing on outcomes that drive real business impact.

What You’ll Learn

• Why value‑driven transformation is replacing cost‑only strategies
• How AI is unlocking new revenue and operational opportunities
• What it means to “go beyond the field” with end‑to‑end service optimization
• How to measure and prove the value of AI in service operations

Going Beyond the Field

True service transformation doesn’t stop with technicians. This conversation explores how organizations are extending service impact across customers, processes, and the broader business—connecting people, processes, and AI to deliver smarter, more scalable outcomes.

Meet Us at Field Service Next – San Diego

The team also shares what they’re looking forward to at Field Service Next, including connecting with peers, customers, and partners who are navigating these same challenges. If you’re attending, stop by booth #215 to continue the conversation.

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Why Should You Listen?

FABCON is where Microsoft Fabric conversations stop being theoretical and start getting real. This year in Atlanta, Hitachi Solutions is on the ground at Booth 545, focused on one thing: helping organizations turn Fabric potential into practical, measurable outcomes.

To kick things off, we recorded a special, on‑site episode of Exchanges with Hitachi Solutions, bringing together a few of the experts you can meet at the booth—and giving you a preview of the conversations we’re having all week at FABCON.

Meet the voices behind the conversation

In this episode, host Matt Volke is joined by:

• Sree Reddy, Senior Data & Analytics Architect, who’s working hands‑on with customers adopting Microsoft Fabric and demonstrating our Empower Data Platform—showing how organizations can simplify architecture, strengthen governance, and move faster with analytics and AI.
• Philip Rainsberger, Solution Sales Professional for Azure Solutions, who brings a business‑first perspective to Fabric adoption—helping teams prioritize initiatives, align stakeholders, and turn capability into real value.
• Carrie Smedira, Solution Sales Professional, who specializes in bridging the gap between AI ambition and business‑ready outcomes. At FABCON, Carrie is focused on helping organizations cut through the hype and zero in on where Microsoft Fabric and AI can drive measurable impact—quickly and responsibly.

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This episode sets the stage for Microsoft FABCON 2026 by spotlighting the people, perspectives, and practical guidance attendees can expect at Booth 545. Host Matt Volke is joined by Philip Rainsberger and Mark Shoesmith of Hitachi Solutions to discuss how organizations are approaching Microsoft Fabric today—what’s driving adoption, where teams get stuck, and how to move from exploration to execution with confidence.

Highlights:

• FABCON is where Microsoft Fabric conversations become practical—shifting from “what’s possible” to “how do we implement and scale this responsibly?”
• Successful Fabric initiatives start with the business problem, not the technology, ensuring data and AI investments are tied to real outcomes.
• Hitachi Solutions’ “thin slice” approach delivers production-ready wins early, avoiding proof-of-concept efforts that never make it to value.
• Common Fabric adoption paths include migrations from on‑prem SQL Server, SSIS, and Synapse Analytics into a unified Fabric architecture.
• Fabric is increasingly the analytics and AI foundation for Dynamics 365 customers, supporting both Finance & Operations and Customer Engagement workloads.
• FABCON attendees are encouraged to come prepared with their current data landscape, top Fabric goals, and key blockers to make booth conversations immediately actionable.

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This episode demystifies AI agents, explaining how they differ from chatbots and showcasing their real-world impact in business applications. Chris Fairfax, Technical Product Manager for Industry Cloud at Hitachi Solutions, shares actionable insights on deploying agents to drive efficiency, empower employees, and unlock new value from enterprise data.

Highlights:

• Agents are AI-powered tools that execute business processes, going beyond simple chatbots by leveraging multiple skills within platforms like Microsoft Dynamics.
• Automation with agents can increase productivity by 20–30%, but the focus is on augmenting—not replacing—employees through human-in-the-loop design.
• Practical use cases include process management, identity verification, call center workflows, and field service automation.
• Data quality and a modern data estate are essential for successful agent deployment and scalability.
• Early wins are seen in industries like insurance, with plans to expand agent capabilities for industry-specific needs.
• Transparency, confidence scores, and purposeful design are key to building trust and driving adoption of AI agents.

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In this episode of Exchanges with Hitachi Solutions, host Ginny Lebeck joins Matt Volke, Chris Satterly, and Mark Shoesmith to preview FabCon 2026 in Atlanta. The conversation explores why FabCon has become a must-attend event for data and AI professionals, how customer expectations around data have evolved, and what organizations need to succeed on their AI journey. Drawing from real-world client conversations and healthcare use cases, the panel discusses Microsoft Fabric as a unifying data platform, the importance of strong data foundations and governance, and how emerging capabilities—from low-code tools to advanced analytics—are enabling teams to move faster and unlock more value from their data. You can find Hitachi Solutions at Fabcoon Booth #545 March 18-20.

Highlights:

• FabCon brings together customers, partners, and Microsoft experts to share practical insights on data management, analytics, and AI, with a strong emphasis on real-world business challenges.
• Organizations are increasingly treating data as a strategic asset rather than a byproduct, focusing on real-time insights, advanced analytics, and AI readiness.
• Microsoft Fabric is emerging as a key enabler, simplifying data ingestion, modeling, and curation while supporting both self-service analytics and advanced data science workloads.
• Healthcare organizations are adopting Fabric to modernize legacy, on-premises data platforms, reduce manual ETL effort, and better handle diverse and high-volume data sources.
• Tools like pipelines, copy jobs, mirroring, and Copilot-assisted development help small data teams work more efficiently and respond faster to analytics demands.
• Strong data models, governance, and curated information are essential prerequisites for successful AI and advanced analytics initiatives.
• Hitachi Solutions’ presence at FabCon focuses on connecting customers with experienced data engineers, data scientists, and industry experts to help translate technology into outcomes.

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Generative AI has captured the imagination of the enterprise world—but the reality is more complex than the hype. In this fireside chat, Stuart Morris, Director of R&D at Hitachi Solutions, joined me to unpack the findings of MIT’s “Gen AI Divide” report and share practical insights from the front lines of AI deployment.

The conversation begins with a sobering statistic: 95% of generative AI pilots fail to deliver measurable impact on P&L. But as Stuart points out, that doesn’t mean they’re worthless. Many projects drive internal process improvements, enhance compliance, and streamline operations—benefits that don’t always show up on a balance sheet but are critical to business success.

In our chat above, Stuart emphasizes that readiness is key. Companies often jump into AI without ensuring their data is clean, organized, and accessible. “There’s no amount of AI you can throw at a data situation that’s in shambles,” he warns. Instead, success starts with foundational work—cleaning up CRM systems, structuring data warehouses, and defining clear business processes.

This discussion highlights a recurring theme: back-office automation consistently delivers higher ROI than customer-facing AI. Internal processes are well-documented and easier to optimize, while public-facing AI carries reputational risks. Stuart shares examples of chatbots behaving badly on social media, underscoring the importance of starting with internal use cases.

Key Takeaways:

• Most AI pilots fail to impact P&L—but still deliver internal value.
• Data readiness is essential; clean, structured data is the foundation.
• Back-office automation offers higher ROI and lower risk than customer-facing AI.
• Targeted, repeatable solutions outperform one-off proofs of concept.
• Avoid vendor lock-in by deploying in customer tenants and delivering code.
• Success lies in purposeful design, tailored agents, and a steady approach to innovation.

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In this episode of Exchanges with Hitachi Solutions, host Matt Volke sat down with Evan Sotos, Engineering Manager for the Empower Data Platform, and Stuart Morris, Director of Research & Development, for a fast‑paced wrap‑up of their time on the ground at CES 2026 in Las Vegas. With Hitachi’s presence spanning IoT, mobility, digital cities, energy, and data innovation, the team shares firsthand observations from the world’s largest consumer electronics event and highlights the trends shaping the year ahead.

In this episode, you’ll hear Evan, and Stuart discuss:

• What it’s like navigating CES across massive halls filled with humanoid robots, batteries, e‑mobility, and next‑generation digital city technologies—and why even three days on the show floor isn’t enough to see it all.
• How Hitachi’s unified booth showcased the full “One Hitachi” vision, bringing together group companies across industries to demonstrate integrated solutions for AI, data, and digital transformation.
• What Empower brings to the CES conversation, including how organizations can unify, orchestrate, and model their data to support analytics, AI, business insights, and industry‑specific use cases.
• Why clean, consolidated data is the foundation for any successful AI initiative, especially as companies discover the limits of rushing into AI without the right data architecture.
• How Hitachi Solutions is applying AI internally first—building real workflows, modernizing processes like RFP response management, and proving value before productizing solutions for customers.
• The industry’s growing focus on pragmatic, value‑driven AI, including a shift away from “toy” demos toward real workflows, hybrid models, and the rise of agentic AI—paired with the need to combine classical automation and machine learning with modern LLMs.

Whether you’re exploring how AI can drive real business transformation, looking to modernize your data foundation, or just curious about the innovations making headlines at CES, this episode offers an insider’s perspective on the technologies and trends expected to define 2026.

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