BigQuery for Data Warehousing
Apress (Verlag)
978-1-4842-6185-9 (ISBN)
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.
Mark Mucchetti is an industry technology leader in healthcare and ecommerce. He has been working with computers and writing software for over 30 years, starting with BASIC and Turbo C on an Intel 8088 and now using Node.js in the cloud. He has been building and managing technology groups for much of that time, combining his deep love of technical topics with his management skills to create world-class platforms. Mark has also worked in databases, release engineering, front- and back-end coding, and project management. He believes that the best decisions are made with the best data available, and that BigQuery is a great technology to increase the value and accessibility of data for business leaders on a day-to-day basis. He has seen the transformation that accurate, timely data has on an organization’s ability to succeed, and wants to bring that knowledge to the world in a people-first way.
Part I. Building a Warehouse.- 1. Settling into BigQuery.- 2. Starting Your Warehouse Project.- 3. All My Data.- 4. Managing BigQuery Costs.- Part II. Filling the Warehouse.- 5. Loading Data Into the Warehouse.- 6. Streaming Data Into the Warehouse.- 7. Dataflow.- Part III. Using the Warehouse.- 8. Care and Feeding of Your Warehouse.- 9. Querying the Warehouse.- 10. Scheduling Jobs.- 11. Serverless Functions with GCP.- 12. Cloud Logging.- Part IV. Maintaining the Warehouse.- 13. Advanced BigQuery.- 14. Data Governance.- 15. Adapting to Long-Term Change.- Part V. Reporting On and Visualizing Your Data.- 16. Reporting.- 17. Dashboards and Visualization.- 18. Google Data Studio.- Part VI. Enhancing Your Data's Potential.- 19. BigQuery ML.- 20. Jupyter Notebooks and Public Datasets.- 21. Conclusion.- 22. Appendix A: Cloud Shell and Cloud SDK.- 23. Appendix B: Sample Project Charter.
| Erscheinungsdatum | 09.10.2020 |
|---|---|
| Zusatzinfo | 99 Illustrations, black and white; XXXV, 525 p. 99 illus. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Informatik ► Software Entwicklung | |
| Schlagworte | Big Data • Big Query • BigQueryML • Data Lake • Data Machine Learning • Data Mart • Data Warehouse • ETL • GCP • Google Cloud Platform • SQL |
| ISBN-10 | 1-4842-6185-2 / 1484261852 |
| ISBN-13 | 978-1-4842-6185-9 / 9781484261859 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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