語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Jumpstart Snowflake = a step-by-step...
~
Anoshin, Dmitry.
FindBook
Google Book
Amazon
博客來
Jumpstart Snowflake = a step-by-step guide to modern cloud analytics /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Jumpstart Snowflake/ by Dmitry Anoshin, Dmitry Shirokov, Donna Strok.
其他題名:
a step-by-step guide to modern cloud analytics /
作者:
Anoshin, Dmitry.
其他作者:
Shirokov, Dmitry.
出版者:
Berkeley, CA :Apress : : 2020.,
面頁冊數:
xiii, 267 p. :ill., digital ;24 cm.
內容註:
Chapter 1: Getting Started with Cloud Analytics- Chapter 2: Getting Started with Snowflake -- Chapter 3: Virtual Warehouse -- Chapter 4: Loading Bulk Data into Snowflake -- Chapter 5: Getting Started with SnowSQL -- Chapter 6: Continuous Data Loading with Snowpipe -- Chapter 7: Snowflake Administration -- Chapter 8: Snowflake Security Overview -- Chapter 9: Working with Semi Structured Data -- Chapter 10: Secure Data Sharing -- Chapter 11: Design Modern Analytics Solution with Snowflake -- Chapter 12: Snowflake and Data Science -- Chapter 13: Migration to Snowflake -- Chapter 14: Time Travel.
Contained By:
Springer eBooks
標題:
Data warehousing. -
電子資源:
https://doi.org/10.1007/978-1-4842-5328-1
ISBN:
9781484253281
Jumpstart Snowflake = a step-by-step guide to modern cloud analytics /
Anoshin, Dmitry.
Jumpstart Snowflake
a step-by-step guide to modern cloud analytics /[electronic resource] :by Dmitry Anoshin, Dmitry Shirokov, Donna Strok. - Berkeley, CA :Apress :2020. - xiii, 267 p. :ill., digital ;24 cm.
Chapter 1: Getting Started with Cloud Analytics- Chapter 2: Getting Started with Snowflake -- Chapter 3: Virtual Warehouse -- Chapter 4: Loading Bulk Data into Snowflake -- Chapter 5: Getting Started with SnowSQL -- Chapter 6: Continuous Data Loading with Snowpipe -- Chapter 7: Snowflake Administration -- Chapter 8: Snowflake Security Overview -- Chapter 9: Working with Semi Structured Data -- Chapter 10: Secure Data Sharing -- Chapter 11: Design Modern Analytics Solution with Snowflake -- Chapter 12: Snowflake and Data Science -- Chapter 13: Migration to Snowflake -- Chapter 14: Time Travel.
Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. You will: Know the key functionalities of Snowflake Set up security and access with cluster Bulk load data into Snowflake using the COPY command Migrate from a legacy data warehouse to Snowflake integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools.
ISBN: 9781484253281
Standard No.: 10.1007/978-1-4842-5328-1doiSubjects--Topical Terms:
606996
Data warehousing.
LC Class. No.: QA76.9.D37 / A567 2020
Dewey Class. No.: 005.745
Jumpstart Snowflake = a step-by-step guide to modern cloud analytics /
LDR
:03066nmm a2200325 a 4500
001
2215363
003
DE-He213
005
20200602105736.0
006
m d
007
cr nn 008maaau
008
201119s2020 cau s 0 eng d
020
$a
9781484253281
$q
(electronic bk.)
020
$a
9781484253274
$q
(paper)
024
7
$a
10.1007/978-1-4842-5328-1
$2
doi
035
$a
978-1-4842-5328-1
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.D37
$b
A567 2020
072
7
$a
UB
$2
bicssc
072
7
$a
COM018000
$2
bisacsh
072
7
$a
UB
$2
thema
082
0 4
$a
005.745
$2
23
090
$a
QA76.9.D37
$b
A615 2020
100
1
$a
Anoshin, Dmitry.
$3
3446667
245
1 0
$a
Jumpstart Snowflake
$h
[electronic resource] :
$b
a step-by-step guide to modern cloud analytics /
$c
by Dmitry Anoshin, Dmitry Shirokov, Donna Strok.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2020.
300
$a
xiii, 267 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
Chapter 1: Getting Started with Cloud Analytics- Chapter 2: Getting Started with Snowflake -- Chapter 3: Virtual Warehouse -- Chapter 4: Loading Bulk Data into Snowflake -- Chapter 5: Getting Started with SnowSQL -- Chapter 6: Continuous Data Loading with Snowpipe -- Chapter 7: Snowflake Administration -- Chapter 8: Snowflake Security Overview -- Chapter 9: Working with Semi Structured Data -- Chapter 10: Secure Data Sharing -- Chapter 11: Design Modern Analytics Solution with Snowflake -- Chapter 12: Snowflake and Data Science -- Chapter 13: Migration to Snowflake -- Chapter 14: Time Travel.
520
$a
Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. You will: Know the key functionalities of Snowflake Set up security and access with cluster Bulk load data into Snowflake using the COPY command Migrate from a legacy data warehouse to Snowflake integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools.
650
0
$a
Data warehousing.
$3
606996
650
0
$a
Cloud computing.
$3
1016782
650
1 4
$a
Computer Applications.
$3
891249
700
1
$a
Shirokov, Dmitry.
$3
3446668
700
1
$a
Strok, Donna.
$3
3446669
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
856
4 0
$u
https://doi.org/10.1007/978-1-4842-5328-1
950
$a
Professional and Applied Computing (Springer-12059)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9390271
電子資源
11.線上閱覽_V
電子書
EB QA76.9.D37 A567 2020
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入