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180516s2018 sz | o |||| 0|eng d |
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|z 9783319769882
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| 020 |
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|a 9783319769899 (online)
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|a (EBZ)ebs17958951e
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4 |
|a QA276-280
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| 100 |
1 |
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|a Stahl, Reinhold.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 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.
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| 250 |
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|a 1st ed. 2018.
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| 264 |
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2018.
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| 505 |
0 |
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|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.
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| 520 |
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|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.
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| 650 |
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0 |
|a Statistics .
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| 650 |
|
0 |
|a Artificial intelligence—Data processing.
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| 650 |
|
0 |
|a Data mining.
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| 650 |
|
0 |
|a Quantitative research.
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| 650 |
|
0 |
|a Big data.
|
| 700 |
1 |
|
|a Staab, Patricia.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
|
| 710 |
2 |
|
|a SpringerLink (Online service)
|
| 773 |
0 |
|
|t Springer Mathematics and Statistics eBooks 2018 English/International
|d Springer Nature
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9783319769882
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9783319769905
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783030083427
|
| 776 |
1 |
|
|t Measuring the Data Universe
|
| 856 |
4 |
0 |
|y Access Content Online(from Springer Mathematics and Statistics eBooks 2018 English/International)
|u https://ezproxy.msu.edu/login?url=https://link.springer.com/10.1007/978-3-319-76989-9
|z Springer Mathematics and Statistics eBooks 2018 English/International: 2018
|
