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Data Exploration and Preparation with BigQuery

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Release : 2023-11-29
Genre : Computers
Kind : eBook
Book Rating : 424/5 ( reviews)

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Book Synopsis Data Exploration and Preparation with BigQuery by : Mike Kahn

Download or read book Data Exploration and Preparation with BigQuery written by Mike Kahn. This book was released on 2023-11-29. Available in PDF, EPUB and Kindle. Book excerpt: Leverage BigQuery to understand and prepare your data to ensure that it's accurate, reliable, and ready for analysis and modeling Key Features Use mock datasets to explore data with the BigQuery web UI, bq CLI, and BigQuery API in the Cloud console Master optimization techniques for storage and query performance in BigQuery Engage with case studies on data exploration and preparation for advertising, transportation, and customer support data Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData professionals encounter a multitude of challenges such as handling large volumes of data, dealing with data silos, and the lack of appropriate tools. Datasets often arrive in different conditions and formats, demanding considerable time from analysts, engineers, and scientists to process and uncover insights. The complexity of the data life cycle often hinders teams and organizations from extracting the desired value from their data assets. Data Exploration and Preparation with BigQuery offers a holistic solution to these challenges. The book begins with the basics of BigQuery while covering the fundamentals of data exploration and preparation. It then progresses to demonstrate how to use BigQuery for these tasks and explores the array of big data tools at your disposal within the Google Cloud ecosystem. The book doesn’t merely offer theoretical insights; it’s a hands-on companion that walks you through properly structuring your tables for query efficiency and ensures adherence to data preparation best practices. You’ll also learn when to use Dataflow, BigQuery, and Dataprep for ETL and ELT workflows. The book will skillfully guide you through various case studies, demonstrating how BigQuery can be used to solve real-world data problems. By the end of this book, you’ll have mastered the use of SQL to explore and prepare datasets in BigQuery, unlocking deeper insights from data.What you will learn Assess the quality of a dataset and learn best practices for data cleansing Prepare data for analysis, visualization, and machine learning Explore approaches to data visualization in BigQuery Apply acquired knowledge to real-life scenarios and design patterns Set up and organize BigQuery resources Use SQL and other tools to navigate datasets Implement best practices to query BigQuery datasets Gain proficiency in using data preparation tools, techniques, and strategies Who this book is for This book is for data analysts seeking to enhance their data exploration and preparation skills using BigQuery. It guides anyone using BigQuery as a data warehouse to extract business insights from large datasets. A basic understanding of SQL, reporting, data modeling, and transformations will assist with understanding the topics covered in this book.

Google BigQuery: The Definitive Guide

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Release : 2019-10-23
Genre : Computers
Kind : eBook
Book Rating : 431/5 ( reviews)

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Book Synopsis Google BigQuery: The Definitive Guide by : Valliappa Lakshmanan

Download or read book Google BigQuery: The Definitive Guide written by Valliappa Lakshmanan. This book was released on 2019-10-23. Available in PDF, EPUB and Kindle. Book excerpt: Work with petabyte-scale datasets while building a collaborative, agile workplace in the process. This practical book is the canonical reference to Google BigQuery, the query engine that lets you conduct interactive analysis of large datasets. BigQuery enables enterprises to efficiently store, query, ingest, and learn from their data in a convenient framework. With this book, you’ll examine how to analyze data at scale to derive insights from large datasets efficiently. Valliappa Lakshmanan, tech lead for Google Cloud Platform, and Jordan Tigani, engineering director for the BigQuery team, provide best practices for modern data warehousing within an autoscaled, serverless public cloud. Whether you want to explore parts of BigQuery you’re not familiar with or prefer to focus on specific tasks, this reference is indispensable.

Strategic Blueprint for Enterprise Analytics

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Kind : eBook
Book Rating : 855/5 ( reviews)

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Book Synopsis Strategic Blueprint for Enterprise Analytics by : Liang Wang

Download or read book Strategic Blueprint for Enterprise Analytics written by Liang Wang. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt:

Data Intensive Computing Applications for Big Data

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Release : 2018-01-31
Genre : Computers
Kind : eBook
Book Rating : 140/5 ( reviews)

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Book Synopsis Data Intensive Computing Applications for Big Data by : M. Mittal

Download or read book Data Intensive Computing Applications for Big Data written by M. Mittal. This book was released on 2018-01-31. Available in PDF, EPUB and Kindle. Book excerpt: The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.

Google Machine Learning and Generative AI for Solutions Architects

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Release : 2024-06-28
Genre : Computers
Kind : eBook
Book Rating : 029/5 ( reviews)

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Book Synopsis Google Machine Learning and Generative AI for Solutions Architects by : Kieran Kavanagh

Download or read book Google Machine Learning and Generative AI for Solutions Architects written by Kieran Kavanagh. This book was released on 2024-06-28. Available in PDF, EPUB and Kindle. Book excerpt: Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectively Key Features Understand key concepts, from fundamentals through to complex topics, via a methodical approach Build real-world end-to-end MLOps solutions and generative AI applications on Google Cloud Get your hands on a code repository with over 20 hands-on projects for all stages of the ML model development lifecycle Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMost companies today are incorporating AI/ML into their businesses. Building and running apps utilizing AI/ML effectively is tough. This book, authored by a principal architect with about two decades of industry experience, who has led cross-functional teams to design, plan, implement, and govern enterprise cloud strategies, shows you exactly how to design and run AI/ML workloads successfully using years of experience from some of the world’s leading tech companies. You’ll get a clear understanding of essential fundamental AI/ML concepts, before moving on to complex topics with the help of examples and hands-on activities. This will help you explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. You’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process. By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.What you will learn Build solutions with open-source offerings on Google Cloud, such as TensorFlow, PyTorch, and Spark Source, understand, and prepare data for ML workloads Build, train, and deploy ML models on Google Cloud Create an effective MLOps strategy and implement MLOps workloads on Google Cloud Discover common challenges in typical AI/ML projects and get solutions from experts Explore vector databases and their importance in Generative AI applications Uncover new Gen AI patterns such as Retrieval Augmented Generation (RAG), agents, and agentic workflows Who this book is for This book is for aspiring solutions architects looking to design and implement AI/ML solutions on Google Cloud. Although this book is suitable for both beginners and experienced practitioners, basic knowledge of Python and ML concepts is required. The book focuses on how AI/ML is used in the real world on Google Cloud. It briefly covers the basics at the beginning to establish a baseline for you, but it does not go into depth on the underlying mathematical concepts that are readily available in academic material.

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