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Practical Implementation of a Data Lake

Translating Customer Expectations into Tangible Technical Goals
BuchKartoniert, Paperback
202 Seiten
Englisch
Springererschienen am04.10.2023First Edition
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. What You Will LearnUnderstand the challenges associated with implementing a data lakeExplore the architectural patterns and processes used to design a new data lakeDesign and implement data lake capabilitiesAssociate business requirements with technical deliverables to drive success Who This Book Is ForData Scientists and Architects, Machine Learning Engineers, and Software Engineers.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR29,95
E-BookPDF1 - PDF WatermarkE-Book
EUR26,99

Produkt

KlappentextThis 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. What You Will LearnUnderstand the challenges associated with implementing a data lakeExplore the architectural patterns and processes used to design a new data lakeDesign and implement data lake capabilitiesAssociate business requirements with technical deliverables to drive success Who This Book Is ForData Scientists and Architects, Machine Learning Engineers, and Software Engineers.
Zusammenfassung
Details
ISBN/GTIN978-1-4842-9734-6
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2023
Erscheinungsdatum04.10.2023
AuflageFirst Edition
Seiten202 Seiten
SpracheEnglisch
IllustrationenXX, 202 p. 58 illus.
Artikel-Nr.54324897

Inhalt/Kritik

Inhaltsverzeichnis
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.mehr
Kritik
"The content of this book is often structured as tables, or as overly extensive bullet lists, and includes numerous illustrations. Well-meant suborning of the original, informal intent may result in producing skeleton checklists ... . The book is explicitly aimed at data scientists and architects, machine learning engineers, and software engineers. Overall, the information provided, once the reader masters its presentation, is valuable for project-leadership-minded individuals ... ." (A. Squassabia, Computing Reviews, February 26, 2024)mehr

Autor


Nayanjyoti Paul is an Associate Director and Chief Azure Architect for GenAI and LLM CoE for Accenture. He is the product owner and creator of a patented asset. Presently, he leads multiple projects as a lead architect around generative AI , large language models, data analytics, and machine learning. Nayan is a certified Master Technology Architect, certified Data Scientist, and certified Databricks Champion with additional AWS and Azure certifications. He is a speaker at conferences like Strata Conference, Data Works Summit, and AWS Reinvent. He also delivers guest lectures at Universities.
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