國立高雄大學圖資館 |

Language: English

Back

Practical implementation of a data laketranslating customer expectations into tangible technical goals /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Practical implementation of a data lakeby Nayanjyoti Paul.
Reminder of title:	translating customer expectations into tangible technical goals /
Author:	Paul, Nayanjyoti.
Published:	Berkeley, CA :Apress :2023.
Description:	xx, 202 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Business intelligence.
Online resource:	https://doi.org/10.1007/978-1-4842-9735-3
ISBN:	9781484297353$q(electronic bk.)

Practical implementation of a data laketranslating customer expectations into tangible technical goals /
Paul, Nayanjyoti.

Practical implementation of a data laketranslating customer expectations into tangible technical goals /[electronic resource] :by Nayanjyoti Paul. - Berkeley, CA :Apress :2023. - xx, 202 p. :ill., digital ;24 cm.

Chapter 1: Understanding the Customer Needs -- Chapter 2: Security Model -- Chapter 3: Organizational Model -- Chapter 4: Data Lake Structure -- Chapter 5: Production Playground -- Chapter 6: Production Operationalization -- Chapter 7: Miscellaneous.

This book explains how to implement a data lake strategy, covering the technical and business challenges architects commonly face. It also illustrates how and why client requirements should drive architectural decisions. Drawing upon a specific case from his own experience, author Nayanjyoti Paul begins with the consideration from which all subsequent decisions should flow: what does your customer need? He also describes the importance of identifying key stakeholders and the key points to focus on when starting a new project. Next, he takes you through the business and technical requirement-gathering process, and how to translate customer expectations into tangible technical goals. From there, you'll gain insight into the security model that will allow you to establish security and legal guardrails, as well as different aspects of security from the end user's perspective. You'll learn which organizational roles need to be onboarded into the data lake, their responsibilities, the services they need access to, and how the hierarchy of escalations should work. Subsequent chapters explore how to divide your data lakes into zones, organize data for security and access, manage data sensitivity, and techniques used for data obfuscation. Audit and logging capabilities in the data lake are also covered before a deep dive into designing data lakes to handle multiple kinds and file formats and access patterns. The book concludes by focusing on production operationalization and solutions to implement a production setup. After completing this book, you will understand how to implement a data lake, the best practices to employ while doing so, and will be armed with practical tips to solve business problems. You will: Understand the challenges associated with implementing a data lake Explore the architectural patterns and processes used to design a new data lake Design and implement data lake capabilities Associate business requirements with technical deliverables to drive success.

ISBN: 9781484297353$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-9735-3doiSubjects--Topical Terms:

202057
Business intelligence.

LC Class. No.: QA76.9.D37

Dewey Class. No.: 005.74

Practical implementation of a data laketranslating customer expectations into tangible technical goals /
LDR:03294nmm a2200325 a 4500 001 652439
003 DE-He213
005 20231003101841.0
006 m d
007 cr nn 008maaau
008 240327s2023 cau s 0 eng d
020 $a 9781484297353$q(electronic bk.)
020 $a 9781484297346$q(paper)
024 7 $a 10.1007/978-1-4842-9735-3 $2 doi
035 $a 978-1-4842-9735-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D37
072 7 $a UN $2 bicssc
072 7 $a COM031000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.74 $2 23
090 $a QA76.9.D37 $b P324 2023
100 1 $a Paul, Nayanjyoti. $3 962972
245 1 0 $a Practical implementation of a data lake $h [electronic resource] : $b translating customer expectations into tangible technical goals / $c by Nayanjyoti Paul.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2023.
300 $a xx, 202 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Understanding the Customer Needs -- Chapter 2: Security Model -- Chapter 3: Organizational Model -- Chapter 4: Data Lake Structure -- Chapter 5: Production Playground -- Chapter 6: Production Operationalization -- Chapter 7: Miscellaneous.
520 $a This book explains how to implement a data lake strategy, covering the technical and business challenges architects commonly face. It also illustrates how and why client requirements should drive architectural decisions. Drawing upon a specific case from his own experience, author Nayanjyoti Paul begins with the consideration from which all subsequent decisions should flow: what does your customer need? He also describes the importance of identifying key stakeholders and the key points to focus on when starting a new project. Next, he takes you through the business and technical requirement-gathering process, and how to translate customer expectations into tangible technical goals. From there, you'll gain insight into the security model that will allow you to establish security and legal guardrails, as well as different aspects of security from the end user's perspective. You'll learn which organizational roles need to be onboarded into the data lake, their responsibilities, the services they need access to, and how the hierarchy of escalations should work. Subsequent chapters explore how to divide your data lakes into zones, organize data for security and access, manage data sensitivity, and techniques used for data obfuscation. Audit and logging capabilities in the data lake are also covered before a deep dive into designing data lakes to handle multiple kinds and file formats and access patterns. The book concludes by focusing on production operationalization and solutions to implement a production setup. After completing this book, you will understand how to implement a data lake, the best practices to employ while doing so, and will be armed with practical tips to solve business problems. You will: Understand the challenges associated with implementing a data lake Explore the architectural patterns and processes used to design a new data lake Design and implement data lake capabilities Associate business requirements with technical deliverables to drive success.
650 0 $a Business intelligence. $3 202057
650 0 $a Data mining. $3 184440
650 0 $a Data warehousing. $3 199894
650 0 $a Management information systems. $3 199355
650 1 4 $a Data Science. $3 913495
650 2 4 $a Python. $3 763308
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Artificial Intelligence. $3 212515
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-9735-3
950 $a Professional and Applied Computing (SpringerNature-12059)