國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Architecting a modern data warehouse...

Amazon Web Services (Firm)

Architecting a modern data warehouse for large enterprisesbuild multi-cloud modern distributed data warehouses with Azure and AWS /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Architecting a modern data warehouse for large enterprisesby Anjani Kumar, Abhishek Mishra, Sanjeev Kumar.
其他題名:	build multi-cloud modern distributed data warehouses with Azure and AWS /
作者:	Kumar, Anjani.
其他作者:	Mishra, Abhishek.
出版者:	Berkeley, CA :Apress :2024.
面頁冊數:	xv, 368 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Big data.
電子資源:	https://doi.org/10.1007/979-8-8688-0029-0
ISBN:	9798868800290$q(electronic bk.)

Architecting a modern data warehouse for large enterprisesbuild multi-cloud modern distributed data warehouses with Azure and AWS /
Kumar, Anjani.

Architecting a modern data warehouse for large enterprisesbuild multi-cloud modern distributed data warehouses with Azure and AWS /[electronic resource] :by Anjani Kumar, Abhishek Mishra, Sanjeev Kumar. - Berkeley, CA :Apress :2024. - xv, 368 p. :ill., digital ;24 cm.

Chapter 1: Introduction -- Chapter 2: Modern Data Warehouses -- Chapter 3: Data Lake, Lake House, and Delta Lake -- Chapter 4: Data Mesh -- Chapter 5: Data Orchestration Techniques -- Chapter 6: Data Democratization, Governance, and Security -- Chapter 7: Business Intelligence.

Design and architect new generation cloud-based data warehouses using Azure and AWS. This book provides an in-depth understanding of how to build modern cloud-native data warehouses, as well as their history and evolution. The book starts by covering foundational data warehouse concepts, and introduces modern features such as distributed processing, big data storage, data streaming, and processing data on the cloud. You will gain an understanding of the synergy, relevance, and usage data warehousing standard practices in the modern world of distributed data processing. The authors walk you through the essential concepts of Data Mesh, Data Lake, Lakehouse, and Delta Lake. And they demonstrate the services and offerings available on Azure and AWS that deal with data orchestration, data democratization, data governance, data security, and business intelligence. After completing this book, you will be ready to design and architect enterprise-grade, cloud-based modern data warehouses using industry best practices and guidelines. You will: Understand the core concepts underlying modern data warehouses Design and build cloud-native data warehouses Gain a practical approach to architecting and building data warehouses on Azure and AWS Implement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and Lakehouse Process data through pandas and evaluate your model's performance using metrics such as F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications.

ISBN: 9798868800290$q(electronic bk.)

Standard No.: 10.1007/979-8-8688-0029-0doiSubjects--Corporate Names:

785206
Amazon Web Services (Firm)
Subjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.D37

Dewey Class. No.: 658.403802855745

Architecting a modern data warehouse for large enterprisesbuild multi-cloud modern distributed data warehouses with Azure and AWS /
LDR:03000nmm a2200325 a 4500 001 661217
003 DE-He213
005 20231227132645.0
006 m d
007 cr nn 008maaau
008 241106s2024 cau s 0 eng d
020 $a 9798868800290$q(electronic bk.)
020 $a 9798868800283$q(paper)
024 7 $a 10.1007/979-8-8688-0029-0 $2 doi
035 $a 979-8-8688-0029-0
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D37
072 7 $a UTC $2 bicssc
072 7 $a COM000000 $2 bisacsh
072 7 $a UTC $2 thema
082 0 4 $a 658.403802855745 $2 23
090 $a QA76.9.D37 $b K96 2024
100 1 $a Kumar, Anjani. $3 855449
245 1 0 $a Architecting a modern data warehouse for large enterprises $h [electronic resource] : $b build multi-cloud modern distributed data warehouses with Azure and AWS / $c by Anjani Kumar, Abhishek Mishra, Sanjeev Kumar.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2024.
300 $a xv, 368 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Introduction -- Chapter 2: Modern Data Warehouses -- Chapter 3: Data Lake, Lake House, and Delta Lake -- Chapter 4: Data Mesh -- Chapter 5: Data Orchestration Techniques -- Chapter 6: Data Democratization, Governance, and Security -- Chapter 7: Business Intelligence.
520 $a Design and architect new generation cloud-based data warehouses using Azure and AWS. This book provides an in-depth understanding of how to build modern cloud-native data warehouses, as well as their history and evolution. The book starts by covering foundational data warehouse concepts, and introduces modern features such as distributed processing, big data storage, data streaming, and processing data on the cloud. You will gain an understanding of the synergy, relevance, and usage data warehousing standard practices in the modern world of distributed data processing. The authors walk you through the essential concepts of Data Mesh, Data Lake, Lakehouse, and Delta Lake. And they demonstrate the services and offerings available on Azure and AWS that deal with data orchestration, data democratization, data governance, data security, and business intelligence. After completing this book, you will be ready to design and architect enterprise-grade, cloud-based modern data warehouses using industry best practices and guidelines. You will: Understand the core concepts underlying modern data warehouses Design and build cloud-native data warehouses Gain a practical approach to architecting and building data warehouses on Azure and AWS Implement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and Lakehouse Process data through pandas and evaluate your model's performance using metrics such as F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications.
610 2 0 $a Amazon Web Services (Firm) $3 785206
650 0 $a Big data. $3 609582
650 0 $a Business enterprises $x Data processing. $3 246238
650 0 $a Data warehousing. $3 199894
650 0 $a Microsoft Azure (Computing platform) $3 763318
650 1 4 $a Cloud Computing. $3 777671
650 2 4 $a Microsoft. $3 915087
650 2 4 $a Computer Communication Networks. $3 218087
700 1 $a Mishra, Abhishek. $3 787965
700 1 $a Kumar, Sanjeev. $3 384316
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/979-8-8688-0029-0
950 $a Professional and Applied Computing (SpringerNature-12059)