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 environment, a...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
[Place of publication not identified] :
Apress
[2020]
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| Edición: | 1st ed. 2020. |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631688106719 |
Tabla de Contenidos:
- 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.
