國立虎尾科技大學 |

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.
面頁冊數:	XVIII, 327 p. 90 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Big data. -
電子資源:	https://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 InsightsHandle Data-Driven Challenges in an Enterprise Big Data Lake /[electronic resource] :by Saurabh Gupta, Venkata Giri. - 1st ed. 2018. - XVIII, 327 p. 90 illus.online resource.

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:

981821
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Practical Enterprise Data Lake Insights = Handle Data-Driven Challenges in an Enterprise Big Data Lake /
LDR:02997nam a22003975i 4500 001 995421
003 DE-He213
005 20200705020903.0
007 cr nn 008mamaa
008 201225s2018 xxu| s |||| 0|eng d
020 $a 9781484235225 $9 978-1-4842-3522-5
024 7 $a 10.1007/978-1-4842-3522-5 $2 doi
035 $a 978-1-4842-3522-5
050 4 $a QA76.9.B45
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.7 $2 23
100 1 $a Gupta, Saurabh. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $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.
250 $a 1st ed. 2018.
264 1 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2018.
300 $a XVIII, 327 p. 90 illus. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
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 Big data. $3 981821
650 0 $a Application software. $3 528147
650 1 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. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1206692
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484235218
776 0 8 $i Printed edition: $z 9781484235232
776 0 8 $i Printed edition: $z 9781484246061
856 4 0 $u https://doi.org/10.1007/978-1-4842-3522-5
912 $a ZDB-2-CWD
912 $a ZDB-2-SXPC
950 $a Professional and Applied Computing (SpringerNature-12059)
950 $a Professional and Applied Computing (R0) (SpringerNature-43716)