## No Python? No problem. Delta Live Tables (DLTs - Lakeflow Declarative Pipelines) brings powerful, production-ready data pipelines to life with just SQL. In this session, we’ll show how analysts and engineers alike can declaratively define robust pipelines – from raw ingestion to analytics-ready data – all without writing a single line of Python.

Using a real-world business scenario and dataset, we’ll walk through how to:

* Ingest data with **schema inference and Auto Loader** into a Bronze layer
* Apply **transformations and quality expectations** in the Silver layer
* Build a **business-friendly Star Schema** in the Gold layer
* Add **data quality tests** directly into your pipeline
* Compare **deployment options** in the UI and via Databricks Asset Bundles (DABs)

Whether you’re a data analyst taking your first steps into engineering or an engineer looking for faster, simpler ways to build pipelines, this session will give you the practical foundation you need to unlock value with DLTs.
**Agenda:**

* 5 min – Welcome & Business Context
* 10 min – Why Delta Live Tables?
* 5 min – Pipeline overview (sources, processing, presentation)
* 10 min – Bronze layer: ingestion, schema inference, expectations
* 5 min – Silver layer: transformations, quality rules
* 5 min – Gold layer: star schema design
* 5 min – Testing in DLT
* 10 min – Deployment: UI vs DABs

UK Databricks User Group | Powered by Champions & Unifeye

Bianca Stratulat

Jordan Begg

Stephen Nicholson

Dave Westgarth

aziz.elharcha

pradeepreddyytr

Jalil

Lyès SARDI

Stefano Barzaghi

Jamie Mach

Abhishek Krishna

Salma hd

Merlyn Nita

kikihao486

Azhar

Xincheng Luo

Vishal Diwase

Building Delta Live Tables (DLTs) Only with SQL

Online event

###

Data without governance is not just unmanageable, it’s a liability. As organisations scale their data platforms across teams, regions, and clouds, the need for consistent governance becomes critical.
In this session, we’ll explore how **Databricks Unity Catalog** provides a unified approach to governance, enabling:

* **Fine-grained access controls** to secure sensitive data while empowering users.
* **Centralised lineage and auditability** for complete visibility across your data estate.
* **Cross-region and multi-team compliance** to meet regulatory requirements without slowing down innovation.

We’ll share **real-world examples** of how enterprises are leveraging Unity Catalog to:

* Reduce risk and prepare for audits.
* Simplify security management at scale.
* Accelerate data democratization with confidence.

Whether you’re a data engineer, architect, or governance lead, this session will provide practical insights into building a trusted data foundation with Unity Catalog.
**Why attend?**
✅ Understand how to operationalise governance at scale
✅ See how leading organisations manage compliance in real-world scenarios
✅ Learn best practices to unlock secure collaboration and faster delivery
Join us to discover how to turn governance from a blocker into an enabler of data and AI success.

Raman Gupta

Unity Catalog & Governance at Scale with Databricks

Enterprises today face increasing pressure to collaborate on data while maintaining security, governance, and regulatory compliance. In this session, we’ll showcase how **Databricks and Palantir** integrate to provide a **powerful foundation for enterprise-scale data collaboration**.
Together, these platforms enable organisations to:

* **Accelerate analytics & AI** by unifying diverse datasets under a secure and governed model.
* **Support decision intelligence** with advanced modelling and shared data applications.
* **Reduce time to value** in highly regulated industries by streamlining compliance and governance.

Through **real-world use cases**, we’ll demonstrate how financial services, healthcare, and public sector organisations are already leveraging the Databricks + Palantir combination to:

* Break down silos while protecting sensitive data.
* Enable collaborative, cross-organisation analytics.
* Deliver insights and innovation faster with confidence.

**Why attend?**
✅ Discover how Databricks and Palantir complement each other in practice
✅ Learn strategies for secure and governed data sharing across teams and partners
✅ See how regulated industries are achieving faster, safer decision-making
Join us to explore the future of **trusted, collaborative data ecosystems** powered by Databricks + Palantir.

Databricks + Palantir: Powering Enterprise Data Collaboration

Many organisations stall at the Proof-of-Concept (PoC) stage, struggling to translate early wins into scalable, business-ready outcomes. This session is designed for **Delivery Managers, Product Owners, and Leaders** who want to move beyond experimentation and deliver lasting value with Databricks.
We’ll explore practical strategies for:

* **Structuring projects** from discovery through production with clear milestones and measurable outcomes.
* **Managing stakeholder expectations** to avoid scope creep and align on success criteria early.
* **Establishing strong delivery governance** to keep projects on track and accountable.
* **Deploying Databricks infrastructure** correctly from the outset — including multi-environment setup (Dev/Test/Prod), Unity Catalog, storage configuration, and CI/CD with Databricks Asset Bundles — to ensure scalable, secure, and reproducible deployments.
* **Avoiding the “never-ending PoC” trap** by creating a clear path to productionisation.

Through **real-world delivery examples**, we’ll show how to combine best practices in project management with modern Databricks capabilities to:

* Accelerate time to value
* De-risk deployments
* Build stakeholder confidence in data & AI programmes

**Why attend?**
✅ Learn how to deliver Databricks projects with clarity and confidence
✅ Understand infrastructure and governance foundations for scalable rollouts
✅ Gain practical tips to move from pilot to production successfully
Join us to learn how to deliver **Databricks projects that don’t just prove value — they scale it.**

 From PoC to Production: Delivering with Confidence with Databricks

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