國立虎尾科技大學 |

Practical implementation of a data lake = translating customer expectations into tangible technical goals /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Practical implementation of a data lake/ by 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

Practical implementation of a data lake = translating 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

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

557121
Business intelligence.

LC Class. No.: QA76.9.D37

Dewey Class. No.: 005.74

Practical implementation of a data lake = translating customer expectations into tangible technical goals /
LDR:03294nam a2200325 a 4500 001 1118004
003 DE-He213
005 20231003101841.0
006 m d
007 cr nn 008maaau
008 240126s2023 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 1432027
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 557121
650 0 $a Data mining. $3 528622
650 0 $a Data warehousing. $3 561693
650 0 $a Management information systems. $3 561123
650 1 4 $a Data Science. $3 1174436
650 2 4 $a Python. $3 1115944
650 2 4 $a Machine Learning. $3 1137723
650 2 4 $a Artificial Intelligence. $3 646849
710 2 $a SpringerLink (Online service) $3 593884
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)