語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Measuring the data universe = data i...
~
Stahl, Reinhold.
FindBook
Google Book
Amazon
博客來
Measuring the data universe = data integration using statistical data and metadata exchange /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Measuring the data universe/ by Reinhold Stahl, Patricia Staab.
其他題名:
data integration using statistical data and metadata exchange /
作者:
Stahl, Reinhold.
其他作者:
Staab, Patricia.
出版者:
Cham :Springer International Publishing : : 2018.,
面頁冊數:
vii, 117 p. :digital ;24 cm.
內容註:
0 About the Authors -- 0 About This Book -- Part 1: Creating Comprehensive Data Worlds using Standardisation -- 1 Where We Stand, Where We Want to Be, and How to Get There -- 2 What Does Reality Look Like? -- 3 What Can We Expect From Big Data? -- 4 Why is Data Integration so Hard? -- 5 Basic Thoughts about Standardisation -- 6 Standardisation and Research -- 7 Introducing Standards Successfully -- 8 Statistics Driving Successful Data Integration -- 9 Contribution of the Statistics Standard SDMX -- 10 Conclusion and Outlook -- Part 2: The Statistics Standard SDMX -- 11 History of SDMX -- 12 The Main Elements of SDMX -- 13 Working With SDMX -- 14 SDMX as a key success factor for data integration -- Glossary.
Contained By:
Springer eBooks
標題:
Data integration (Computer science) -
電子資源:
http://dx.doi.org/10.1007/978-3-319-76989-9
ISBN:
9783319769899
Measuring the data universe = data integration using statistical data and metadata exchange /
Stahl, Reinhold.
Measuring the data universe
data integration using statistical data and metadata exchange /[electronic resource] :by Reinhold Stahl, Patricia Staab. - Cham :Springer International Publishing :2018. - vii, 117 p. :digital ;24 cm.
0 About the Authors -- 0 About This Book -- Part 1: Creating Comprehensive Data Worlds using Standardisation -- 1 Where We Stand, Where We Want to Be, and How to Get There -- 2 What Does Reality Look Like? -- 3 What Can We Expect From Big Data? -- 4 Why is Data Integration so Hard? -- 5 Basic Thoughts about Standardisation -- 6 Standardisation and Research -- 7 Introducing Standards Successfully -- 8 Statistics Driving Successful Data Integration -- 9 Contribution of the Statistics Standard SDMX -- 10 Conclusion and Outlook -- Part 2: The Statistics Standard SDMX -- 11 History of SDMX -- 12 The Main Elements of SDMX -- 13 Working With SDMX -- 14 SDMX as a key success factor for data integration -- Glossary.
This richly illustrated book provides an easy-to-read introduction to the challenges of organizing and integrating modern data worlds, explaining the contribution of public statistics and the ISO standard SDMX (Statistical Data and Metadata Exchange) As such, it is a must for data experts as well those aspiring to become one. Today, exponentially growing data worlds are increasingly determining our professional and private lives. The rapid increase in the amount of globally available data, fueled by search engines and social networks but also by new technical possibilities such as Big Data, offers great opportunities. But whatever the undertaking - driving the block chain revolution or making smart phones even smarter - success will be determined by how well it is possible to integrate, i.e. to collect, link and evaluate, the required data. One crucial factor in this is the introduction of a cross-domain order system in combination with a standardization of the data structure. Using everyday examples, the authors show how the concepts of statistics provide the basis for the universal and standardized presentation of any kind of information. They also introduce the international statistics standard SDMX, describing the profound changes it has made possible and the related order system for the international statistics community.
ISBN: 9783319769899
Standard No.: 10.1007/978-3-319-76989-9doiSubjects--Topical Terms:
1565903
Data integration (Computer science)
LC Class. No.: QA76.9.D338 / S734 2018
Dewey Class. No.: 005.74
Measuring the data universe = data integration using statistical data and metadata exchange /
LDR
:03002nmm a2200289 a 4500
001
2146207
003
DE-He213
005
20181129154936.0
006
m d
007
cr nn 008maaau
008
190227s2018 gw s 0 eng d
020
$a
9783319769899
$q
(electronic bk.)
020
$a
9783319769882
$q
(paper)
024
7
$a
10.1007/978-3-319-76989-9
$2
doi
035
$a
978-3-319-76989-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.D338
$b
S734 2018
082
0 4
$a
005.74
$2
23
090
$a
QA76.9.D338
$b
S781 2018
100
1
$a
Stahl, Reinhold.
$3
3332565
245
1 0
$a
Measuring the data universe
$h
[electronic resource] :
$b
data integration using statistical data and metadata exchange /
$c
by Reinhold Stahl, Patricia Staab.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
vii, 117 p. :
$b
digital ;
$c
24 cm.
505
0
$a
0 About the Authors -- 0 About This Book -- Part 1: Creating Comprehensive Data Worlds using Standardisation -- 1 Where We Stand, Where We Want to Be, and How to Get There -- 2 What Does Reality Look Like? -- 3 What Can We Expect From Big Data? -- 4 Why is Data Integration so Hard? -- 5 Basic Thoughts about Standardisation -- 6 Standardisation and Research -- 7 Introducing Standards Successfully -- 8 Statistics Driving Successful Data Integration -- 9 Contribution of the Statistics Standard SDMX -- 10 Conclusion and Outlook -- Part 2: The Statistics Standard SDMX -- 11 History of SDMX -- 12 The Main Elements of SDMX -- 13 Working With SDMX -- 14 SDMX as a key success factor for data integration -- Glossary.
520
$a
This richly illustrated book provides an easy-to-read introduction to the challenges of organizing and integrating modern data worlds, explaining the contribution of public statistics and the ISO standard SDMX (Statistical Data and Metadata Exchange) As such, it is a must for data experts as well those aspiring to become one. Today, exponentially growing data worlds are increasingly determining our professional and private lives. The rapid increase in the amount of globally available data, fueled by search engines and social networks but also by new technical possibilities such as Big Data, offers great opportunities. But whatever the undertaking - driving the block chain revolution or making smart phones even smarter - success will be determined by how well it is possible to integrate, i.e. to collect, link and evaluate, the required data. One crucial factor in this is the introduction of a cross-domain order system in combination with a standardization of the data structure. Using everyday examples, the authors show how the concepts of statistics provide the basis for the universal and standardized presentation of any kind of information. They also introduce the international statistics standard SDMX, describing the profound changes it has made possible and the related order system for the international statistics community.
650
0
$a
Data integration (Computer science)
$3
1565903
650
1 4
$a
Statistics.
$3
517247
650
2 4
$a
Applied Statistics.
$3
3300946
650
2 4
$a
Data Structures.
$3
891009
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
898250
650
2 4
$a
Big Data/Analytics.
$3
2186785
650
2 4
$a
Big Data.
$3
3134868
700
1
$a
Staab, Patricia.
$3
3332566
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-76989-9
950
$a
Mathematics and Statistics (Springer-11649)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9347723
電子資源
11.線上閱覽_V
電子書
EB QA76.9.D338 S734 2018
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入