Modeling for success: Building data structures that last скачать в хорошем качестве

Modeling for success: Building data structures that last

Poor data modeling is one of the most common and costly mistakes teams make when implementing dbt. Quick fixes and one-off designs may seem faster in the moment, but they create hidden risks: redundant code, fragile pipelines, and data that’s hard to trust or scale. A well-designed model is the foundation for sustainable analytics. Join experts from dbt Labs and phData as they share proven strategies for structuring models that align to business processes, reduce complexity, and keep projects future-ready. You’ll learn why dimensional modeling is the most effective approach for dbt’s batch-oriented workflows, and how intentional design pays dividends in speed, cost, and trust. What you’ll gain from watching: -Clarity on modeling approaches: Compare dimensional, data vault, relational, and one-big-table models, and learn when each makes sense -Best practices in action: See examples of good and bad modeling decisions, and their impact on scalability, cost, and governance -A blueprint for success: Learn how to translate business requirements into technical designs that evolve with your needs -Real-world insights: Hear stories from experts who’ve guided dozens of dbt implementations—what works, what doesn’t, and why modeling right matters most Meet your speakers: -Dustin Dorsey, Data Engineering Director at phData -Dakota Kelley, Principal Solutions Architect at phData -Stephen Robb, Partner Solutions Architect at dbt Labs Chapters: 00:00 Welcome and Introduction 01:14 Housekeeping and Event Details 02:01 Series Overview and Today's Theme 03:40 Meet the Presenters 05:14 Introduction to Data Modeling 10:45 Data Modeling Paradigms 13:50 Common Data Modeling Patterns 21:27 Dimensional Modeling Deep Dive 36:46 Building Business Processes to the Lowest Level of Granularity 37:21 Importance of Stakeholder Meetings and Iterative Documentation 37:48 High-Level Overview of dbt Functionality 38:35 Translating Business Needs into Fact Tables 39:53 Identifying Business Entities as Dimensions 41:50 Creating Fact Tables for Business Processes 45:55 Understanding Dimensions in Dimensional Models 49:11 Dialogue with Stakeholders: Sales Data Needs 51:08 Dialogue with Stakeholders: Customer Information 52:58 Dialogue with Stakeholders: Product Performance 54:03 Dialogue with Stakeholders: Tracking Time 56:30 Connecting Sales Info to Customers, Products, and Dates 58:04 Summarizing Insights and Best Practices 01:02:16 Real-World Lessons and Importance of Strong Modeling 01:06:46 Next Steps and Closing Remarks