Data lakes (Record no. 68393)

000 -LEADER
fixed length control field 04775cam a2200529Ia 4500
001 - CONTROL NUMBER
control field on1151184484
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711203158.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200418s2020 enk ob 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119720430
-- (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119720435
-- (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119720423
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119720427
082 04 - CLASSIFICATION NUMBER
Call Number 005.7
245 00 - TITLE STATEMENT
Title Data lakes
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication London :
Publisher ISTE, Ltd. ;
Place of publication Hoboken :
Publisher Wiley,
Year of publication 2020.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (249 p.)
490 1# - SERIES STATEMENT
Series statement Computer engineering series, databases and big data set ;
500 ## - GENERAL NOTE
Remark 1 Description based upon print version of record.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Cover -- Half-Title Page -- Dedication -- Title Page -- Copyright Page -- Contents -- Preface -- 1. Introduction to Data Lakes: Definitions and Discussions -- 1.1. Introduction to data lakes -- 1.2. Literature review and discussion -- 1.3. The data lake challenges -- 1.4. Data lakes versus decision-making systems -- 1.5. Urbanization for data lakes -- 1.6. Data lake functionalities -- 1.7. Summary and concluding remarks -- 2. Architecture of Data Lakes -- 2.1. Introduction -- 2.2. State of the art and practice -- 2.2.1. Definition -- 2.2.2. Architecture -- 2.2.3. Metadata
505 8# - FORMATTED CONTENTS NOTE
Remark 2 2.2.4. Data quality -- 2.2.5. Schema-on-read -- 2.3. System architecture -- 2.3.1. Ingestion layer -- 2.3.2. Storage layer -- 2.3.3. Transformation layer -- 2.3.4. Interaction layer -- 2.4. Use case: the Constance system -- 2.4.1. System overview -- 2.4.2. Ingestion layer -- 2.4.3. Maintenance layer -- 2.4.4. Query layer -- 2.4.5. Data quality control -- 2.4.6. Extensibility and flexibility -- 2.5. Concluding remarks -- 3. Exploiting Software Product Lines and Formal Concept Analysis for the Design of Data Lake Architectures -- 3.1. Our expectations -- 3.2. Modeling data lake functionalities
505 8# - FORMATTED CONTENTS NOTE
Remark 2 3.3. Building the knowledge base of industrial data lakes -- 3.4. Our formalization approach -- 3.5. Applying our approach -- 3.6. Analysis of our first results -- 3.7. Concluding remarks -- 4. Metadata in Data Lake Ecosystems -- 4.1. Definitions and concepts -- 4.2. Classification of metadata by NISO -- 4.2.1. Metadata schema -- 4.2.2. Knowledge base and catalog -- 4.3. Other categories of metadata -- 4.3.1. Business metadata -- 4.3.2. Navigational integration -- 4.3.3. Operational metadata -- 4.4. Sources of metadata -- 4.5. Metadata classification -- 4.6. Why metadata are needed
505 8# - FORMATTED CONTENTS NOTE
Remark 2 4.6.1. Selection of information (re)sources -- 4.6.2. Organization of information resources -- 4.6.3. Interoperability and integration -- 4.6.4. Unique digital identification -- 4.6.5. Data archiving and preservation -- 4.7. Business value of metadata -- 4.8. Metadata architecture -- 4.8.1. Architecture scenario 1: point-to-point metadata architecture -- 4.8.2. Architecture scenario 2: hub and spoke metadata architecture -- 4.8.3. Architecture scenario 3: tool of record metadata architecture -- 4.8.4. Architecture scenario 4: hybrid metadata architecture
505 8# - FORMATTED CONTENTS NOTE
Remark 2 4.8.5. Architecture scenario 5: federated metadata architecture -- 4.9. Metadata management -- 4.10. Metadata and data lakes -- 4.10.1. Application and workload layer -- 4.10.2. Data layer -- 4.10.3. System layer -- 4.10.4. Metadata types -- 4.11. Metadata management in data lakes -- 4.11.1. Metadata directory -- 4.11.2. Metadata storage -- 4.11.3. Metadata discovery -- 4.11.4. Metadata lineage -- 4.11.5. Metadata querying -- 4.11.6. Data source selection -- 4.12. Metadata and master data management -- 4.13. Conclusion -- 5. A Use Case of Data Lake Metadata Management -- 5.1. Context
500 ## - GENERAL NOTE
Remark 1 5.1.1. Data lake definition
700 1# - AUTHOR 2
Author 2 Laurent, Anne,
700 1# - AUTHOR 2
Author 2 Laurent, Dominique.
700 1# - AUTHOR 2
Author 2 Madera, Cédrine.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1002/9781119720430
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Big data.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Databases.
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Big data.
-- (OCoLC)fst01892965
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Databases.
-- (OCoLC)fst00888065
994 ## -
-- 92
-- DG1

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