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BigQuery for Data Warehousing: Managed Data Analysis in the Google Cloud de Mark Mucchetti

BigQuery for Data Warehousing: Managed Data Analysis in the Google Cloud

Autor Mark Mucchetti
en Limba Engleză Paperback – oct 2020
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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Specificații

ISBN-13: 9781484261859
ISBN-10: 1484261852
Pagini: 525
Ilustrații: XXXV, 525 p. 99 illus.
Dimensiuni: 178 x 254 x 36 mm
Greutate: 1.06 kg
Ediția:1st ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States

Cuprins

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.

Notă biografică

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.

Textul de pe ultima copertă

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.

You will:
  • 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

Caracteristici

Explains how to load or stream your business data into BigQuery Suggests innovative ways to engage with business stakeholders for the long run Provides suggestions for enhancement of data analysis via machine learning