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BigQuery for data warehousing : managed data analysis in the Google cloud /
Create a data warehouse, complete with reporting and dashboards using Google's BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environme...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Santa Monica, CA :
APress,
[2020]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 505 | 0 | |a Intro -- Table of Contents -- About the Author -- About the Technical Reviewer -- Acknowledgments -- Introduction -- Part I: Building a Warehouse -- Chapter 1: Settling into BigQuery -- Getting Started with GCP -- Beginning with GCP -- Using Google Cloud Platform -- The Cloud Console -- The Command-Line Interface -- Programmatic Access -- BigQuery in the Cloud Console -- Querying -- Tables -- Aliasing -- Commenting -- SELECT -- FROM -- WHERE -- GROUP BY -- ORDER BY -- LIMIT -- Additional Things to Try -- Shortcuts -- Statement Batches -- Query History -- Saving Queries and Views | |
| 505 | 8 | |a Scheduled Queries -- Designing Your Warehouse -- Google BigQuery As a Data Store -- Row-Oriented Approach -- Column-Oriented Approach -- Google BigQuery As a Data Warehouse -- Key Questions -- Fundamentals -- What Problem Am I Trying to Solve? -- What Is the Scope of This Problem? -- Who Will Be the Primary Users of Your Warehouse? -- Are You Replacing Something That Exists Already? -- Thinking About Scale -- How Much Data Do I Have Today? -- How Quickly Will My Data Increase in Size? -- How Many Readers Am I Going to Have? -- How Many Analysts Am I Going to Have? -- What Is My Budget? | |
| 505 | 8 | |a Do I Need to Account for Real-Time Data? -- Data Normalization -- Summary -- Chapter 2: Starting Your Warehouse Project -- Where to Start -- Key Questions -- What Are My Finite Resources? -- What Is My Business Domain? -- What Differentiates My Business from Others in Its Domain? -- Who Knows What Data I Need? -- Who Already Knows What Data They Need? -- What Are My Key Entities? -- What Are My Key Relationships? -- What Role Does Time Play in My Model? -- What Role Does Cost Play in My Model? -- General Considerations -- Making the Case -- Interviewing Stakeholders -- Resolving Conflicts | |
| 505 | 8 | |a Compiling Documentation -- Sources of Truth -- Data Dictionary -- The Charter -- Understanding Business Acceptance -- Recording Decisions -- Choosing a Design -- Transactional Store -- Star/Snowflake Schemas -- NoSQL -- BigQuery -- Understanding the BigQuery Model -- Projects -- Datasets -- Tables -- Normalization/Denormalization -- Hierarchical Data Structure -- Partitioning -- Summary -- Chapter 3: All My Data -- The Data Model -- Intake Rates -- Value of Historical Data -- Creating the Data Model -- Making a Dataset -- Creating Tables -- Source -- Empty -- Google Cloud Storage -- Upload | |
| 505 | 8 | |a Drive -- Google Cloud Bigtable -- Format -- CSV -- JSONL -- Avro -- Parquet/ORC -- Destination -- A Little Aside on Naming Things -- Schema -- STRING -- BYTES -- INTEGER -- FLOAT -- NUMERIC -- BOOLEAN -- TIMESTAMP -- DATE -- TIME -- GEOGRAPHY -- ARRAY -- STRUCT (RECORD) -- Mode -- Partition and Cluster Settings -- Advanced Options -- Partitioning -- Partitioning by Integer -- Clustering -- Reading from BigQuery -- BigQuery UI -- bq Command Line -- BigQuery API -- BigQuery Storage API -- Summary -- Chapter 4: Managing BigQuery Costs -- The BigQuery Model -- BigQuery Cost Models -- Storage Pricing | |
| 504 | |a Includes bibliographical references. | ||
| 520 | |a Create a data warehouse, complete with reporting and dashboards using Google's BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environment, and then mine and analyze that data for insight into making your business more successful. You will gain practical knowledge about how to use BigQuery to solve data challenges in your organization. BigQuery is a managed cloud platform from Google that provides enterprise data warehousing and reporting capabilities. Part I of this book shows you how to design and provision a data warehouse in the BigQuery platform. Part II teaches you how to load and stream your operational data into the warehouse to make it ready for analysis and reporting. Parts III and IV cover querying and maintaining, helping you keep your information relevant with other Google Cloud Platform services and advanced BigQuery. Part V takes reporting to the next level by showing you how to create dashboards to provide at-a-glance visual representations of your business situation. Part VI provides an introduction to data science with BigQuery, covering machine learning and Jupyter notebooks. What You Will Learn Design a data warehouse for your project or organization Load data from a variety of external and internal sources Integrate other Google Cloud Platform services for more complex workflows Maintain and scale your data warehouse as your organization grows Analyze, report, and create dashboards on the information in the warehouse Become familiar with machine learning techniques using BigQuery ML Who This Book Is For Developers who want to provide business users with fast, reliable, and insightful analysis from operational data, and data analysts interested in a cloud-based solution that avoids the pain of provisioning their own servers. | ||
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