Databricks Data Intelligence Platform
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Databricks Data Intelligence Platform
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.
Databricks Certified Data Engineer Associate Study Guide
Author: Derar Alhussein
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2024-04-24
Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform. In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests. Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks! You'll learn how to: Use the Databricks Platform and Delta Lake effectively Perform advanced ETL tasks using Apache Spark SQL Design multi-hop architecture to process data incrementally Build production pipelines using Delta Live Tables and Databricks Jobs Implement data governance using Databricks SQL and Unity Catalog Derar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications.
Databricks ML in Action
Author: Stephanie Rivera
language: en
Publisher: Packt Publishing Ltd
Release Date: 2024-05-17
Get to grips with autogenerating code, deploying ML algorithms, and leveraging various ML lifecycle features on the Databricks Platform, guided by best practices and reusable code for you to try, alter, and build on Key Features Build machine learning solutions faster than peers only using documentation Enhance or refine your expertise with tribal knowledge and concise explanations Follow along with code projects provided in GitHub to accelerate your projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDiscover what makes the Databricks Data Intelligence Platform the go-to choice for top-tier machine learning solutions. Written by a team of industry experts at Databricks with decades of combined experience in big data, machine learning, and data science, Databricks ML in Action presents cloud-agnostic, end-to-end examples with hands-on illustrations of executing data science, machine learning, and generative AI projects on the Databricks Platform. You’ll develop expertise in Databricks' managed MLflow, Vector Search, AutoML, Unity Catalog, and Model Serving as you learn to apply them practically in everyday workflows. This Databricks book not only offers detailed code explanations but also facilitates seamless code importation for practical use. You’ll discover how to leverage the open-source Databricks platform to enhance learning, boost skills, and elevate productivity with supplemental resources. By the end of this book, you'll have mastered the use of Databricks for data science, machine learning, and generative AI, enabling you to deliver outstanding data products.What you will learn Set up a workspace for a data team planning to perform data science Monitor data quality and detect drift Use autogenerated code for ML modeling and data exploration Operationalize ML with feature engineering client, AutoML, VectorSearch, Delta Live Tables, AutoLoader, and Workflows Integrate open-source and third-party applications, such as OpenAI's ChatGPT, into your AI projects Communicate insights through Databricks SQL dashboards and Delta Sharing Explore data and models through the Databricks marketplace Who this book is for This book is for machine learning engineers, data scientists, and technical managers seeking hands-on expertise in implementing and leveraging the Databricks Data Intelligence Platform and its Lakehouse architecture to create data products.