Iain Dobson
Data Engineer, Quorum
Edinburgh, United Kingdom
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Iain is a seasoned IT professional with over two decades of experience. Based in an employee-owned IT consultancy in the heart of Scotland, he views his role more as a vocation than a job, as it continually presents new learnings and opportunities to meet interesting, intelligent people with shared interests.
Believing in the transformative power of IT, learning, and data, Iain advocates for ethical and accessible IT solutions to drive change. He combines technical proficiency with a passion for sharing knowledge with the IT community.
Area of Expertise
Topics
Using ChatGPT to accelerate your data project
ChatGPT has taken the world by storm with its ability to generate text, but it can also be used to assist your data project by helping design your database schema, write high quality SQL scripts, create Python code to link to external web services, and even design ADF dataflows. This session is designed to show you some of these key capabilities and how they can be used to accelerate your data project and also as a great learning tool for your own professional development.
Optimising Azure Architecture: A Deep Dive into Service and Private Endpoints
Knowing how to effectively implement Azure network services for security and performance requires a proper understanding of when to use Azure Service Endpoints and Private Endpoints.
This presentation provides an overview of each endpoint type and discusses the benefits and drawbacks of each. Attendees will learn how to make informed decisions on usage, avoid common pitfalls, and apply best practices for a secure Azure environment.
While the session delves deeply into the technical aspects, we will start from the basics, introducing networking components at a beginner level to ensure everyone can follow along. This approach ensures that even those new to endpoint security will grasp the foundational concepts before we explore the advanced topics.
Automating Quality: Infrastructure and Data Validation via Azure DevOps Pipelines
As cloud systems grow complex and data becomes vital to decisions, reliable deployments demand automated quality checks at every stage. This talk demonstrates how to embed infrastructure and data validations into your CI/CD workflows. While Azure DevOps is the example platform, the concepts and patterns apply equally to GitHub Actions, GitLab, and other tools.
By blending PowerShell-based infrastructure tests (via Pester) with data validations (via Great Expectations), you’ll learn how to structure tests, manage secrets, parameterise for multiple environments, and generate actionable outputs. The result is a resilient, transparent pipeline that fosters trust, continuous improvement, and shared ownership.
Talk Structure:
1. Setting the Stage: Why post-deployment testing matters and how it aligns with DevOps values.
2. Infrastructure Validation: Ensuring resource integrity and configurations with Pester.
3. Data Quality Checks: Validating assumptions and maintaining data integrity with Great Expectations.
4. Practical Integration: Step-by-step guidance for embedding these tests in Azure DevOps YAML pipelines.
5. Scaling & Culture: How automated checks reinforce a blameless culture, reliability, and team empowerment.
Relevance:
* DevOps Practitioners: Learn patterns to improve release quality.
* Culturally Minded Leaders: See how embedding checks fosters trust and shared ownership.
* Data Teams: Ensure data integrity for accurate analytics and ML workflows.
Format:
A mix of conceptual explanation, hands-on demonstration, and practical examples-no vendor pitches, just proven methods and open-source tools.
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