語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Practical enterprise data lake insig...
~
Giri, Venkata.
Practical enterprise data lake insights = handle data-driven challenges in an enterprise big data lake /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Practical enterprise data lake insights/ by Saurabh Gupta, Venkata Giri.
其他題名:
handle data-driven challenges in an enterprise big data lake /
作者:
Gupta, Saurabh.
其他作者:
Giri, Venkata.
出版者:
Berkeley, CA :Apress : : 2018.,
面頁冊數:
xviii, 327 p. :digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
Electronic data processing - Distributed processing -
電子資源:
http://dx.doi.org/10.1007/978-1-4842-3522-5
ISBN:
9781484235225
Practical enterprise data lake insights = handle data-driven challenges in an enterprise big data lake /
Gupta, Saurabh.
Practical enterprise data lake insights
handle data-driven challenges in an enterprise big data lake /[electronic resource] :by Saurabh Gupta, Venkata Giri. - Berkeley, CA :Apress :2018. - xviii, 327 p. :digital ;24 cm.
Chapter 1: Introduction to Enterprise Data Lakes -- Chapter 2: Data Lake Ingestion Strategies -- Chapter - 3: Capture Streaming Data with Change-Data-Capture -- Chapter 4: Data Processing Strategies in Data Lakes -- Chapter 5: Data Archiving Strategies in Data Lakes -- Chapter 6: Data Security in Data Lakes -- Chapter 7: Ensuring High-Availability of Data Lakes -- Chapter 8: Managing Data Lake Operations.
Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues. When designing an enterprise data lake you often hit a roadblock when you must leave the comfort of the relational world and learn the nuances of handling non-relational data. Starting from sourcing data into the Hadoop ecosystem, you will go through stages that can bring up tough questions such as data processing, data querying, and security. Concepts such as change data capture and data streaming are covered. The book takes an end-to-end solution approach in a data lake environment that includes data security, high availability, data processing, data streaming, and more. Each chapter includes application of a concept, code snippets, and use case demonstrations to provide you with a practical approach. You will learn the concept, scope, application, and starting point. What You'll Learn: Get to know data lake architecture and design principles Implement data capture and streaming strategies Implement data processing strategies in Hadoop Understand the data lake security framework and availability model.
ISBN: 9781484235225
Standard No.: 10.1007/978-1-4842-3522-5doiSubjects--Topical Terms:
1071703
Electronic data processing
--Distributed processing
LC Class. No.: QA76.9.D5 / G878 2018
Dewey Class. No.: 004.36
Practical enterprise data lake insights = handle data-driven challenges in an enterprise big data lake /
LDR
:02554nam a2200289 a 4500
001
927416
003
DE-He213
005
20190115112442.0
006
m d
007
cr nn 008maaau
008
190626s2018 cau s 0 eng d
020
$a
9781484235225
$q
(electronic bk.)
020
$a
9781484235218
$q
(paper)
024
7
$a
10.1007/978-1-4842-3522-5
$2
doi
035
$a
978-1-4842-3522-5
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.D5
$b
G878 2018
082
0 4
$a
004.36
$2
23
090
$a
QA76.9.D5
$b
G977 2018
100
1
$a
Gupta, Saurabh.
$3
1102299
245
1 0
$a
Practical enterprise data lake insights
$h
[electronic resource] :
$b
handle data-driven challenges in an enterprise big data lake /
$c
by Saurabh Gupta, Venkata Giri.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2018.
300
$a
xviii, 327 p. :
$b
digital ;
$c
24 cm.
505
0
$a
Chapter 1: Introduction to Enterprise Data Lakes -- Chapter 2: Data Lake Ingestion Strategies -- Chapter - 3: Capture Streaming Data with Change-Data-Capture -- Chapter 4: Data Processing Strategies in Data Lakes -- Chapter 5: Data Archiving Strategies in Data Lakes -- Chapter 6: Data Security in Data Lakes -- Chapter 7: Ensuring High-Availability of Data Lakes -- Chapter 8: Managing Data Lake Operations.
520
$a
Use this practical guide to successfully handle the challenges encountered when designing an enterprise data lake and learn industry best practices to resolve issues. When designing an enterprise data lake you often hit a roadblock when you must leave the comfort of the relational world and learn the nuances of handling non-relational data. Starting from sourcing data into the Hadoop ecosystem, you will go through stages that can bring up tough questions such as data processing, data querying, and security. Concepts such as change data capture and data streaming are covered. The book takes an end-to-end solution approach in a data lake environment that includes data security, high availability, data processing, data streaming, and more. Each chapter includes application of a concept, code snippets, and use case demonstrations to provide you with a practical approach. You will learn the concept, scope, application, and starting point. What You'll Learn: Get to know data lake architecture and design principles Implement data capture and streaming strategies Implement data processing strategies in Hadoop Understand the data lake security framework and availability model.
650
0
$a
Electronic data processing
$x
Distributed processing
$x
Management.
$3
1071703
650
0
$a
Big data.
$3
981821
650
0
$a
Information storage and retrieval systems.
$3
561170
650
1 4
$a
Computer Science.
$3
593922
650
2 4
$a
Big Data.
$3
1017136
650
2 4
$a
Computer Applications.
$3
669785
650
2 4
$a
Big Data/Analytics.
$3
1106909
700
1
$a
Giri, Venkata.
$3
1206692
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4842-3522-5
950
$a
Professional and Applied Computing (Springer-12059)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入