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2020-Q1 2026-Q1

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Despite claims to the contrary, dimensional modelling and star schemas are alive and well the in the modern data world. But whilst developers might have great technical skills and understand how to build a star schema, they may lack the business domain knowledge to ensure that what they deliver is fit for use by analysts and self-service users. On the flip side, these end users often know what they want and need from a data platform, but struggle to explain this in a way that makes it easy for developers to implement.

How can we improve the requirements gathering process to make sure we avoid the tensions that can arise from this?

This session will cover a data modelling requirements approach that looks to bridge the gap between business and IT by using an end-to-end process for working with business users to collaboratively design a dimensional model, making sure you build super star schemas and turn your self into a data modelling superstar.

About Johnny: Johnny currently works as a data and analytics consultant. He’s been working with Business Intelligence software since 2007, specialising in full stack data platform development since 2016. He’s a self-confessed Business Intelligence geek and in his spare time runs the website, SubStack and YouTube channel Greyskull Analytics, where he likes to nerd out about all things data.

Business Intelligence with Databricks SQL

Discover the power of business intelligence through Databricks SQL. This comprehensive guide explores the features and tools of the Databricks Lakehouse Platform, emphasizing how it leverages data lakes and warehouses for scalable analytics. You'll gain hands-on experience with Databricks SQL, enabling you to manage data efficiently and implement cutting-edge analytical solutions. What this Book will help me do Comprehend the core features of Databricks SQL and its role in the Lakehouse architecture. Master the use of Databricks SQL for conducting scalable and efficient data queries. Implement data management techniques, including security and cataloging, with Databricks. Optimize data performance using Delta Lake and Photon technologies with Databricks SQL. Compose advanced SQL scripts for robust data ingestion and analytics workflows. Author(s) Vihag Gupta, acclaimed data engineer and BI expert, brings a wealth of experience in large-scale data analytics to this work. With a career deeply rooted in cutting-edge data warehousing technologies, Vihag combines expertise with an approachable teaching style. This book reflects his commitment to empowering data professionals with tools for next-gen analytics. Who is it for? Ideal for data engineers, business intelligence analysts, and warehouse administrators aiming to enhance their practice with Databricks SQL. This book suits those with fundamental knowledge of SQL and data platforms seeking to adopt Lakehouse methodologies. Whether a novice to Databricks or looking to master advanced features, this guide will support professional growth.