DataBricks · Event

PalTech at Databricks Data+AI Innovation Summit 2026

From governed data to proactive intelligence. Meet the team operationalizing AI-ready Databricks ecosystems for the enterprise.

Agentic AI Data Intelligence Enterprise AI
Date
June 15 – 18, 2026
Venue
San Francisco
Why this matters

From Data & AI to Data Intelligence.

Databricks has evolved beyond a unified analytics platform. For many enterprises, it is becoming the foundation for data intelligence, bringing together data engineering, analytics, governance, AI, and business intelligence on a single platform.

The conversation is no longer just about building Lakehouses or scaling data pipelines. The focus is shifting toward making enterprise data trusted, governed, discoverable, and actionable for business users, analysts, applications, and AI systems alike.

As organizations accelerate AI adoption, they are increasingly looking to connect data modernization efforts with business outcomes. This is driving new conversations around data intelligence, AI readiness, real-time decision-making, and democratized access to insights.

This is the shift PalTech helps enterprises make. We partner with organizations across healthcare, life sciences, financial services, retail, and technology to turn modern data platforms into trusted, governed, AI-ready foundations the business can act on by connecting data strategy, governance, analytics, and AI to measurable outcomes rather than infrastructure alone. The given four themes frame where we see that value being created.

01

Data Intelligence

Connecting data, analytics, and AI to create a unified foundation for enterprise decision-making.

02

AI & Generative AI

Moving beyond experimentation to operationalize AI and GenAI across business workflows and applications.

03

Governance & Trust

Establishing trusted data through governance, quality, lineage, observability, and responsible AI practices.

04

Real-Time & Democratized Analytics

Enabling business users to access insights faster through conversational analytics, self-service experiences, and real-time intelligence.

Looking Forward

What We Are Looking Forward To

The conversations shaping this year's Data + AI Summit closely mirror the challenges and opportunities we see across our client engagements. Organizations are working to connect data modernization efforts with AI adoption, improve trust in enterprise data, democratize access to insights, and create more intelligent decision-making ecosystems.

As we engage with data, analytics, and AI leaders at the event, we look forward to exchanging perspectives on how enterprises are operationalizing AI, evolving governance strategies, enabling conversational analytics, and building data foundations that can support long-term innovation.

Key questions we are exploring:

  • How do enterprises move from modern data platforms to true data intelligence?
  • What separates successful AI adoption from AI experimentation?
  • How can organizations democratize access to data without compromising governance and trust?
  • What does it take to turn real-time data into real-time decisions?

The next chapter of enterprise transformation will not be defined by how much data organizations collect, but by how effectively they can turn that data into trusted, actionable intelligence. We look forward to learning from the experiences, successes, and perspectives shared across the Databricks community.

What We Help You Build

What We Bring to the Table

Many organizations have already invested in modern data platforms. The challenge now is realizing measurable business value from those investments. At PalTech, we work with enterprises that are navigating the next phase of the data journey transforming modern data platforms into trusted foundations for analytics, AI, and decision-making.

Our experience across healthcare, life sciences, financial services, retail, and technology has shown that successful transformation requires more than platform implementation. It requires connecting data strategy, governance, analytics, and AI to tangible business outcomes. In practice, that work spans data modernization and lakehouse transformation, just-in-time and proactive analytics, data democratization, chat-with-data and conversational analytics, AI and decision intelligence, data governance and trust, and DataOps, MLOps, and platform engineering.

Turning Data Platforms into Business Outcomes

Lakehouse modernization, FinOps, and platform engineering — 70% faster processing, 40% higher productivity, lower cost.

Bridging Data Modernization and AI Adoption

Connecting Lakehouse investments to AI: chat-with-data, RAG knowledge discovery, predictive and proactive analytics.

Making Data More Accessible and Actionable

Self-service and conversational analytics, real-time insight, and governed access for every business user.

Building for Scale, Trust, and Long-Term Value

Governance, data quality, lineage, and observability (Unity Catalog) on DataOps/MLOps foundations.

Who Is Attending

Meet our leadership at Summit.

Rohan Lam

SVP, AI and Digital · PalTech

Rohan Lam brings more than two decades of experience in enterprise AI, digital transformation, data modernization, and large-scale technology transformation.

At Databricks Summit 2026, Rohan will be engaging with enterprise leaders on AI-ready data foundations, DataBricks, Cortex AI, governance-led transformation, conversational analytics, AI-DLC, agentified data operations, and real-time decision intelligence.

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