This book is your comprehensive guide to building robust Generative AI solutions using the Databricks Data Intelligence Platform. Databricks is the fastest-growing data platform offering unified analytics and AI capabilities within a single governance framework, enabling organizations to streamline their data processing workflows, from ingestion to visualization. Additionally, Databricks provides features to train a high-quality large language model (LLM), whether you are looking for Retrieval-Augmented Generation (RAG) or fine-tuning.
Databricks offers a scalable and efficient solution for processing large volumes of both structured and unstructured data, facilitating advanced analytics, machine learning, and real-time processing. In today's GenAI world, Databricks plays a crucial role in empowering organizations to extract value from their data effectively, driving innovation and gaining a competitive edge in the digital age. This book will not only help you master the Data Intelligence Platform but also help power your enterprise to the next level with a bespoke LLM unique to your organization.
Beginning with foundational principles, the book starts with a platform overview and explores features and best practices for ingestion, transformation, and storage with Delta Lake. Advanced topics include leveraging Databricks SQL for querying and visualizing large datasets, ensuring data governance and security with Unity Catalog, and deploying machine learning and LLMs using Databricks MLflow for GenAI. Through practical examples, insights, and best practices, this book equips solution architects and data engineers with the knowledge to design and implement scalable data solutions, making it an indispensable resource for modern enterprises.
Whether you are new to Databricks and trying to learn a new platform, a seasoned practitioner building data pipelines, data science models, or GenAI applications, or even an executive who wants to communicate the value of Databricks to customers, this book is for you. With its extensive feature and best practice deep dives, it also serves as an excellent reference guide if you are preparing for Databricks certification exams.
What You Will Learn
- Foundational principles of Lakehouse architecture
- Key features including Unity Catalog, Databricks SQL (DBSQL), and Delta Live Tables
- Databricks Intelligence Platform and key functionalities
- Building and deploying GenAI Applications from data ingestion to model serving
- Databricks pricing, platform security, DBRX, and many more topics
Who This Book Is For
Solution architects, data engineers, data scientists, Databricks practitioners, and anyone who wants to deploy their Gen AI solutions with the Data Intelligence Platform. This is also a handbook for senior execs who need to communicate the value of Databricks to customers. People who are new to the Databricks Platform and want comprehensive insights will find the book accessible.
Nikhil Gupta is a seasoned data professional with over 18 years of experience in big data technologies, driving innovation and strategic growth in the field. As a Solution Architect at Databricks, he leverages his expertise to help customers across various industries, including retail, CPG, financial services, banking, and manufacturing, modernize their data and AI implementations on the Databricks platform. His expertise spans a range of big data technologies, including data warehousing, data lakes, and real-time data processing, making him a trusted advisor for Fortune 500 companies.
Jason Yip is a data and machine learning architect. He currently serves as Director of Data and AI at Tredence, a leading data science and analytics company. He advises Fortune 500 companies on implementing data and Generative AI strategies on the cloud. He serves on multiple advisory boards at Databricks, including the Partner Product Advisory Board, and the Solution Architect Champion Advisory board. He is a top voice on Databricks and a former Microsoft employee who successfully led the Microsoft Corporate Finance big data transformation using Databricks.
