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Kategorie szczegółowe BISAC

Measuring the Data Universe: Data Integration Using Statistical Data and Metadata Exchange

ISBN-13: 9783030083427 / Angielski / Miękka / 2019 / 117 str.

Reinhold Stahl; Patricia Staab
Measuring the Data Universe: Data Integration Using Statistical Data and Metadata Exchange Stahl, Reinhold 9783030083427 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Measuring the Data Universe: Data Integration Using Statistical Data and Metadata Exchange

ISBN-13: 9783030083427 / Angielski / Miękka / 2019 / 117 str.

Reinhold Stahl; Patricia Staab
cena 242,07
(netto: 230,54 VAT:  5%)

Najniższa cena z 30 dni: 231,29
Termin realizacji zamówienia:
ok. 22 dni roboczych
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Kategorie:
Nauka, Matematyka
Kategorie BISAC:
Mathematics > Prawdopodobieństwo i statystyka
Computers > Data Science - Data Modeling & Design
Computers > Data Science - Data Analytics
Wydawca:
Springer
Język:
Angielski
ISBN-13:
9783030083427
Rok wydania:
2019
Wydanie:
Softcover Repri
Ilość stron:
117
Waga:
0.19 kg
Wymiary:
23.39 x 15.6 x 0.69
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Glosariusz/słownik
Wydanie ilustrowane

"This book offers data professionals an introduction to data standardization-specifically the Statistical Data and Metadata Exchange (SDMX) standard. ... This book would be of most interest to standardization organizations and their staff. Summing Up: Recommended. Professional." (H. Levkowitz, Choice, Vol. 56 (7), March, 2019)

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

Reinhold Stahl, mathematician, has worked at the Statistics Directorate of the German Federal Bank since 1985. He was responsible for the creation of the Federal Bank’s statistical information system in its current form, before becoming Director of General Statistics in 2014. He has been actively involved in the international success story of the SDMX standard presented in this book since its beginnings and has introduced this standard into the statistics of the German Federal Bank. The opportunities opened up by the standardization have made him a passionate advocate of this approach.

Dr. Patricia Staab, mathematician, started working at the Statistics Directorate of the German Federal Bank in 2000, and immediately took part in creating the internal statistical information system based on the SDMX standard. Since then, she has been appointed Head of the German Federal Bank’s Statistical Information Management division. Both the standard and the information system based on it have developed substantially since the beginning, but the effects the standardization could deliver at that time left a lasting impression on her.

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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