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  1. Hands-on enterprise Java microservices with Eclipse MicroProfile
    build and optimize your microservice architecture with Java
    Author: Saavedra, Cesar; Rupp, Heiko W.; Mesnil, Jeff; Loffay, Pavol
    Published: [August 2019]; © 2019
    Publisher:  Packt, Birmingham ; Mumbai

    Location:
    Humboldt-Universität zu Berlin, Universitätsbibliothek, Jacob-und-Wilhelm-Grimm-Zentrum
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    Volltext (URL des Erstveröffentlichers)
    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781838644321
    Subjects: COMPUTERS / Programming Languages / Java; COMPUTERS / Web / Web Services & APIs; Eclipse 4.4; Java 2 Micro Edition
    Scope: 1 Online-Ressource (v, 231 Seiten), Illustrationen (teilweise farbig)
  2. Hands-on enterprise Java microservices with Eclipse MicroProfile
    build and optimize your microservice architecture with Java
    Author: Saavedra, Cesar; Rupp, Heiko W.; Mesnil, Jeff; Loffay, Pavol
    Published: [August 2019]; © 2019
    Publisher:  Packt, Birmingham ; Mumbai

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    Hochschulbibliothek Ingolstadt
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    Universität der Bundeswehr München, Universitätsbibliothek
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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9781838644321
    Subjects: COMPUTERS / Programming Languages / Java; COMPUTERS / Web / Web Services & APIs; Java 2 Micro Edition; Eclipse 4.4
    Scope: 1 Online-Ressource (v, 231 Seiten), Illustrationen (teilweise farbig)
  3. Using the Google Places API and Google Trends data to develop high frequency indicators of economic activity
    Author: Austin, Paul; Marini, Marco; Sanchez, Alberto; Simpson-Bell, Chima; Tebrake, James
    Published: Dec 2021
    Publisher:  International Monetary Fund, Washington, DC

    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest... more

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    Orient-Institut Beirut
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    Online
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    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Potsdamer Straße
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    Universitätsbibliothek Braunschweig
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    Bibliothek der Pädagogischen Hochschule Freiburg/Breisgau
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    Niedersächsische Staats- und Universitätsbibliothek Göttingen
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    Universitäts- und Landesbibliothek Sachsen-Anhalt / Zentrale
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    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    Technische Universität Hamburg, Universitätsbibliothek
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    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
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    Duale Hochschule Baden-Württemberg Heidenheim, Bibliothek
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    e-Book Nationallizenz
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    Thüringer Universitäts- und Landesbibliothek
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    Fachhochschule Kiel, Zentralbibliothek
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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    VS 301
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    Universitätsbibliothek Leipzig
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    Leuphana Universität Lüneburg, Medien- und Informationszentrum, Universitätsbibliothek
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    Duale Hochschule Baden-Württemberg Mosbach, Bibliothek
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    E-Book Nationallizenz IMF
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    Hochschule Offenburg, University of Applied Sciences, Bibliothek Campus Offenburg
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    E-Book International Monetary Fund
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    Hochschule Albstadt-Sigmaringen, Bibliothek Sigmaringen
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    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest in real time data to provide early signals of turning points in economic activity. In this paper, we examine how data extracted from the Google Places API and Google Trends can be used to develop high frequency indicators aligned to the statistical concepts, classifications, and definitions used in producing official measures. The approach is illustrated by use of Google data-derived indicators that predict well the GDP trajectories of selected countries during the early stage of COVID-19. To this end, we developed a methodological toolkit for national compilers interested in using Google data to enhance the timeliness and frequency of economic indicators

     
    Export to reference management software   RIS file
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  4. Hands-on enterprise Java microservices with Eclipse MicroProfile :
    build and optimize your microservice architecture with Java /
    Author: Saavedra, Cesar; Rupp, Heiko W.; Mesnil, Jeff; Loffay, Pavol
    Published: [August 2019].; © 2019.
    Publisher:  Packt,, Birmingham ; Mumbai :

    Location:
    Humboldt-Universität zu Berlin, Universitätsbibliothek, Jacob-und-Wilhelm-Grimm-Zentrum
    Inter-library loan:
    Unlimited inter-library loan, copies and loan
    Export to reference management software   RIS file
      BibTeX file
    Content information
    Volltext (URL des Erstveröffentlichers)
    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 978-1-83864-432-1
    Subjects: COMPUTERS / Programming Languages / Java; COMPUTERS / Web / Web Services & APIs; Java 2 Micro Edition.; Eclipse 4.4.
    Scope: 1 Online-Ressource (v, 231 Seiten) :, Illustrationen (teilweise farbig).
  5. Using the Google Places API and Google Trends data to develop high frequency indicators of economic activity
    Author: Austin, Paul; Marini, Marco; Sanchez, Alberto; Simpson-Bell, Chima; Tebrake, James
    Published: Dec 2021
    Publisher:  International Monetary Fund, Washington, DC

    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest... more

    Access:
    Verlag (kostenfrei)
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)
    Verlag (kostenfrei)

    Location:
    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
    Inter-library loan:
    Unlimited inter-library loan, copies and loan

     

    As the pandemic heigthened policymakers' demand for more frequent and timely indicators to assess economic activities, traditional data collection and compilation methods to produce official indicators are falling short-triggering stronger interest in real time data to provide early signals of turning points in economic activity. In this paper, we examine how data extracted from the Google Places API and Google Trends can be used to develop high frequency indicators aligned to the statistical concepts, classifications, and definitions used in producing official measures. The approach is illustrated by use of Google data-derived indicators that predict well the GDP trajectories of selected countries during the early stage of COVID-19. To this end, we developed a methodological toolkit for national compilers interested in using Google data to enhance the timeliness and frequency of economic indicators

     
    Export to reference management software   RIS file
      BibTeX file