國立虎尾科技大學 |

Practical Data Science = A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Practical Data Science/ by Andreas François Vermeulen.
其他題名:	A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /
作者:	Vermeulen, Andreas François.
面頁冊數:	XXV, 805 p. 57 illus., 9 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Data mining. -
電子資源:	https://doi.org/10.1007/978-1-4842-3054-1
ISBN:	9781484230541

Practical Data Science = A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /
Vermeulen, Andreas François.

Practical Data ScienceA Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /[electronic resource] :by Andreas François Vermeulen. - 1st ed. 2018. - XXV, 805 p. 57 illus., 9 illus. in color.online resource.

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 Report Super Step -- .

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 in Practical Data Science is 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 and dimensions. What You'll Learn: Become fluent in the essential concepts and terminology of data science and data engineering 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.

ISBN: 9781484230541

Standard No.: 10.1007/978-1-4842-3054-1doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Practical Data Science = A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets /
LDR:02783nam a22004095i 4500 001 995867
003 DE-He213
005 20200706033719.0
007 cr nn 008mamaa
008 201225s2018 xxu| s |||| 0|eng d
020 $a 9781484230541 $9 978-1-4842-3054-1
024 7 $a 10.1007/978-1-4842-3054-1 $2 doi
035 $a 978-1-4842-3054-1
050 4 $a QA76.9.D343
072 7 $a UNF $2 bicssc
072 7 $a COM021030 $2 bisacsh
072 7 $a UNF $2 thema
072 7 $a UYQE $2 thema
082 0 4 $a 006.312 $2 23
100 1 $a Vermeulen, Andreas François. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1267234
245 1 0 $a Practical Data Science $h [electronic resource] : $b A Guide to Building the Technology Stack for Turning Data Lakes into Business Assets / $c by Andreas François Vermeulen.
250 $a 1st ed. 2018.
264 1 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2018.
300 $a XXV, 805 p. 57 illus., 9 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a 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 Report Super Step -- .
520 $a 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 in Practical Data Science is 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 and dimensions. What You'll Learn: Become fluent in the essential concepts and terminology of data science and data engineering 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.
650 0 $a Data mining. $3 528622
650 0 $a Big data. $3 981821
650 0 $a Data structures (Computer science). $3 680370
650 1 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Big Data/Analytics. $3 1106909
650 2 4 $a Big Data. $3 1017136
650 2 4 $a Data Storage Representation. $3 669777
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484230534
776 0 8 $i Printed edition: $z 9781484230558
776 0 8 $i Printed edition: $z 9781484248218
856 4 0 $u https://doi.org/10.1007/978-1-4842-3054-1
912 $a ZDB-2-CWD
912 $a ZDB-2-SXPC
950 $a Professional and Applied Computing (SpringerNature-12059)
950 $a Professional and Applied Computing (R0) (SpringerNature-43716)