國立高雄大學圖資館 |

Language: English

Back

BigQuery for data warehousingmanaged...

Mucchetti, Mark.

BigQuery for data warehousingmanaged data analysis in the Google Cloud /

Record Type:	Electronic resources : Monograph/item
Title/Author:	BigQuery for data warehousingby Mark Mucchetti.
Reminder of title:	managed data analysis in the Google Cloud /
Author:	Mucchetti, Mark.
Published:	Berkeley, CA :Apress :2020.
Description:	xxxv, 525 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Data warehousing.
Online resource:	https://doi.org/10.1007/978-1-4842-6186-6
ISBN:	9781484261866$q(electronic bk.)

BigQuery for data warehousingmanaged data analysis in the Google Cloud /
Mucchetti, Mark.

BigQuery for data warehousingmanaged data analysis in the Google Cloud /[electronic resource] :by Mark Mucchetti. - Berkeley, CA :Apress :2020. - xxxv, 525 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9781484261866$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-6186-6doiSubjects--Topical Terms:

199894
Data warehousing.

LC Class. No.: QA76.9.D37 / M83 2020

Dewey Class. No.: 005.745

BigQuery for data warehousingmanaged data analysis in the Google Cloud /
LDR:03647nmm a2200337 a 4500 001 586397
003 DE-He213
005 20210201113726.0
006 m d
007 cr nn 008maaau
008 210323s2020 cau s 0 eng d
020 $a 9781484261866$q(electronic bk.)
020 $a 9781484261859$q(paper)
024 7 $a 10.1007/978-1-4842-6186-6 $2 doi
035 $a 978-1-4842-6186-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D37 $b M83 2020
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
072 7 $a UMT $2 thema
082 0 4 $a 005.745 $2 23
090 $a QA76.9.D37 $b M942 2020
100 1 $a Mucchetti, Mark. $3 877821
245 1 0 $a BigQuery for data warehousing $h [electronic resource] : $b managed data analysis in the Google Cloud / $c by Mark Mucchetti.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2020.
300 $a xxxv, 525 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
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. 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.
650 0 $a Data warehousing. $3 199894
650 1 4 $a Database Management. $3 273994
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-6186-6
950 $a Professional and Applied Computing (SpringerNature-12059)