Please use this identifier to cite or link to this item:
http://localhost/handle/Hannan/2705
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vermeulen, Andreas Franeois. ; author. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:40:04Z | - |
dc.date.available | 2020-05-17T08:40:04Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9781484230541 ; 978-1-4842-3054-1 ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/2705 | - |
dc.description | en_US | |
dc.description | Printed edition: ; 9781484230534 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | 42 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description.abstract | Learn 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.statementofresponsibility | by Andreas Franeois Vermeulen. | en_US |
dc.description.tableofcontents | Chapter 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.extent | XXV, 805 p. 57 illus., 9 illus. in color. ; online resource. ; | en_US |
dc.publisher | Apress : | en_US |
dc.publisher | Imprint: Apress, | en_US |
dc.relation.haspart | 9781484230541.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Big data. ; | en_US |
dc.subject | Data structures (Computer science). ; | en_US |
dc.subject | Data Mining | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Data Mining and Knowledge Discovery | en_US |
dc.subject | Big Data/Analytics. ; | en_US |
dc.subject | Big Data. ; | en_US |
dc.subject | Data Storage Representation. ; | en_US |
dc.title | Practical Data Science | en_US |
dc.title.alternative | A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets / | en_US |
dc.type | Book | en_US |
dc.publisher.place | Berkeley, CA : | en_US |
dc.classification.lc | QA76.9.D343 ; | en_US |
dc.classification.dc | 006.312 ; 23 ; | en_US |
Appears in Collections: | مهندسی فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9781484230541.pdf | 7.75 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vermeulen, Andreas Franeois. ; author. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:40:04Z | - |
dc.date.available | 2020-05-17T08:40:04Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9781484230541 ; 978-1-4842-3054-1 ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/2705 | - |
dc.description | en_US | |
dc.description | Printed edition: ; 9781484230534 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | 42 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description.abstract | Learn 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.statementofresponsibility | by Andreas Franeois Vermeulen. | en_US |
dc.description.tableofcontents | Chapter 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.extent | XXV, 805 p. 57 illus., 9 illus. in color. ; online resource. ; | en_US |
dc.publisher | Apress : | en_US |
dc.publisher | Imprint: Apress, | en_US |
dc.relation.haspart | 9781484230541.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Big data. ; | en_US |
dc.subject | Data structures (Computer science). ; | en_US |
dc.subject | Data Mining | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Data Mining and Knowledge Discovery | en_US |
dc.subject | Big Data/Analytics. ; | en_US |
dc.subject | Big Data. ; | en_US |
dc.subject | Data Storage Representation. ; | en_US |
dc.title | Practical Data Science | en_US |
dc.title.alternative | A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets / | en_US |
dc.type | Book | en_US |
dc.publisher.place | Berkeley, CA : | en_US |
dc.classification.lc | QA76.9.D343 ; | en_US |
dc.classification.dc | 006.312 ; 23 ; | en_US |
Appears in Collections: | مهندسی فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9781484230541.pdf | 7.75 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vermeulen, Andreas Franeois. ; author. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:40:04Z | - |
dc.date.available | 2020-05-17T08:40:04Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9781484230541 ; 978-1-4842-3054-1 ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/2705 | - |
dc.description | en_US | |
dc.description | Printed edition: ; 9781484230534 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | 42 ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description.abstract | Learn 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.statementofresponsibility | by Andreas Franeois Vermeulen. | en_US |
dc.description.tableofcontents | Chapter 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.extent | XXV, 805 p. 57 illus., 9 illus. in color. ; online resource. ; | en_US |
dc.publisher | Apress : | en_US |
dc.publisher | Imprint: Apress, | en_US |
dc.relation.haspart | 9781484230541.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Big data. ; | en_US |
dc.subject | Data structures (Computer science). ; | en_US |
dc.subject | Data Mining | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Data Mining and Knowledge Discovery | en_US |
dc.subject | Big Data/Analytics. ; | en_US |
dc.subject | Big Data. ; | en_US |
dc.subject | Data Storage Representation. ; | en_US |
dc.title | Practical Data Science | en_US |
dc.title.alternative | A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets / | en_US |
dc.type | Book | en_US |
dc.publisher.place | Berkeley, CA : | en_US |
dc.classification.lc | QA76.9.D343 ; | en_US |
dc.classification.dc | 006.312 ; 23 ; | en_US |
Appears in Collections: | مهندسی فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9781484230541.pdf | 7.75 MB | Adobe PDF | Preview File |