Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/2705
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dc.contributor.authorVermeulen, Andreas Franeois. ; author. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:40:04Z-
dc.date.available2020-05-17T08:40:04Z-
dc.date.issued2018en_US
dc.identifier.isbn9781484230541 ; 978-1-4842-3054-1 ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/2705-
dc.descriptionen_US
dc.descriptionPrinted edition: ; 9781484230534 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.description42 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractLearn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated inePractical Data Scienceeis built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types andedimensions. What You'll Learn: Become fluent in the essential concepts and terminology of data science and data engineeringe Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results. ;en_US
dc.description.statementofresponsibilityby Andreas Franeois Vermeulen.en_US
dc.description.tableofcontentsChapter 1: Data Science Technology Stack -- Chapter 2: Vermeulen - Krennwallner - Hillman - Clark -- Chapter 3: Layered Framework -- Chapter 4: Business Layer -- Chapter 5: Utility Layer -- Chapter 6: Three Management Layers -- Chapter 7: Retrieve Super Step -- Chapter 8: Assess Super Step -- Chapter 9: Process Super Step -- Chapter 10: Transform Super Step -- Chapter 11: Organize and Reporte Super Step.-e. ;en_US
dc.format.extentXXV, 805 p. 57 illus., 9 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484230541.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectBig data. ;en_US
dc.subjectData structures (Computer science). ;en_US
dc.subjectData Miningen_US
dc.subjectComputer Scienceen_US
dc.subjectData Mining and Knowledge Discoveryen_US
dc.subjectBig Data/Analytics. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectData Storage Representation. ;en_US
dc.titlePractical Data Scienceen_US
dc.title.alternativeA Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.lcQA76.9.D343 ;en_US
dc.classification.dc006.312 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

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Full metadata record
DC FieldValueLanguage
dc.contributor.authorVermeulen, Andreas Franeois. ; author. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:40:04Z-
dc.date.available2020-05-17T08:40:04Z-
dc.date.issued2018en_US
dc.identifier.isbn9781484230541 ; 978-1-4842-3054-1 ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/2705-
dc.descriptionen_US
dc.descriptionPrinted edition: ; 9781484230534 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.description42 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractLearn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated inePractical Data Scienceeis built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types andedimensions. What You'll Learn: Become fluent in the essential concepts and terminology of data science and data engineeringe Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results. ;en_US
dc.description.statementofresponsibilityby Andreas Franeois Vermeulen.en_US
dc.description.tableofcontentsChapter 1: Data Science Technology Stack -- Chapter 2: Vermeulen - Krennwallner - Hillman - Clark -- Chapter 3: Layered Framework -- Chapter 4: Business Layer -- Chapter 5: Utility Layer -- Chapter 6: Three Management Layers -- Chapter 7: Retrieve Super Step -- Chapter 8: Assess Super Step -- Chapter 9: Process Super Step -- Chapter 10: Transform Super Step -- Chapter 11: Organize and Reporte Super Step.-e. ;en_US
dc.format.extentXXV, 805 p. 57 illus., 9 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484230541.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectBig data. ;en_US
dc.subjectData structures (Computer science). ;en_US
dc.subjectData Miningen_US
dc.subjectComputer Scienceen_US
dc.subjectData Mining and Knowledge Discoveryen_US
dc.subjectBig Data/Analytics. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectData Storage Representation. ;en_US
dc.titlePractical Data Scienceen_US
dc.title.alternativeA Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.lcQA76.9.D343 ;en_US
dc.classification.dc006.312 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484230541.pdf7.75 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorVermeulen, Andreas Franeois. ; author. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:40:04Z-
dc.date.available2020-05-17T08:40:04Z-
dc.date.issued2018en_US
dc.identifier.isbn9781484230541 ; 978-1-4842-3054-1 ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/2705-
dc.descriptionen_US
dc.descriptionPrinted edition: ; 9781484230534 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.description42 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractLearn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated inePractical Data Scienceeis built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types andedimensions. What You'll Learn: Become fluent in the essential concepts and terminology of data science and data engineeringe Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results. ;en_US
dc.description.statementofresponsibilityby Andreas Franeois Vermeulen.en_US
dc.description.tableofcontentsChapter 1: Data Science Technology Stack -- Chapter 2: Vermeulen - Krennwallner - Hillman - Clark -- Chapter 3: Layered Framework -- Chapter 4: Business Layer -- Chapter 5: Utility Layer -- Chapter 6: Three Management Layers -- Chapter 7: Retrieve Super Step -- Chapter 8: Assess Super Step -- Chapter 9: Process Super Step -- Chapter 10: Transform Super Step -- Chapter 11: Organize and Reporte Super Step.-e. ;en_US
dc.format.extentXXV, 805 p. 57 illus., 9 illus. in color. ; online resource. ;en_US
dc.publisherApress :en_US
dc.publisherImprint: Apress,en_US
dc.relation.haspart9781484230541.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectBig data. ;en_US
dc.subjectData structures (Computer science). ;en_US
dc.subjectData Miningen_US
dc.subjectComputer Scienceen_US
dc.subjectData Mining and Knowledge Discoveryen_US
dc.subjectBig Data/Analytics. ;en_US
dc.subjectBig Data. ;en_US
dc.subjectData Storage Representation. ;en_US
dc.titlePractical Data Scienceen_US
dc.title.alternativeA Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /en_US
dc.typeBooken_US
dc.publisher.placeBerkeley, CA :en_US
dc.classification.lcQA76.9.D343 ;en_US
dc.classification.dc006.312 ; 23 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9781484230541.pdf7.75 MBAdobe PDFThumbnail
Preview File