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This open access book provides a comprehensive view on data
ecosystems and platform economics from methodical and technological
foundations up to reports from practical implementations and
applications in various industries. To this end, the book is
structured in four parts: Part I "Foundations and Contexts"
provides a general overview about building, running, and governing
data spaces and an introduction to the IDS and GAIA-X projects.
Part II "Data Space Technologies" subsequently details various
implementation aspects of IDS and GAIA-X, including eg data usage
control, the usage of blockchain technologies, or semantic data
integration and interoperability. Next, Part III describes various
"Use Cases and Data Ecosystems" from various application areas such
as agriculture, healthcare, industry, energy, and mobility. Part IV
eventually offers an overview of several "Solutions and
Applications", eg including products and experiences from companies
like Google, SAP, Huawei, T-Systems, Innopay and many more.
Overall, the book provides professionals in industry with an
encompassing overview of the technological and economic aspects of
data spaces, based on the International Data Spaces and Gaia-X
initiatives. It presents implementations and business cases and
gives an outlook to future developments. In doing so, it aims at
proliferating the vision of a social data market economy based on
data spaces which embrace trust and data sovereignty.
This open access book provides a comprehensive view on data
ecosystems and platform economics from methodical and technological
foundations up to reports from practical implementations and
applications in various industries. To this end, the book is
structured in four parts: Part I "Foundations and Contexts"
provides a general overview about building, running, and governing
data spaces and an introduction to the IDS and GAIA-X projects.
Part II "Data Space Technologies" subsequently details various
implementation aspects of IDS and GAIA-X, including eg data usage
control, the usage of blockchain technologies, or semantic data
integration and interoperability. Next, Part III describes various
"Use Cases and Data Ecosystems" from various application areas such
as agriculture, healthcare, industry, energy, and mobility. Part IV
eventually offers an overview of several "Solutions and
Applications", eg including products and experiences from companies
like Google, SAP, Huawei, T-Systems, Innopay and many more.
Overall, the book provides professionals in industry with an
encompassing overview of the technological and economic aspects of
data spaces, based on the International Data Spaces and Gaia-X
initiatives. It presents implementations and business cases and
gives an outlook to future developments. In doing so, it aims at
proliferating the vision of a social data market economy based on
data spaces which embrace trust and data sovereignty.
Daten sind die strategische Ressource des 21. Jahrhunderts. Es
findet kein Geschaftsprozess, keine Kommunikation zwischen
Geschaftspartnern, keine Wertschoepfung statt, ohne dass die
involvierten Personen, Maschinen und IT-Systeme Daten nutzen,
erzeugen oder verandern. Trends wie die Digitalisierung, Industrie
4.0 und Social Media tragen ebenfalls dazu bei, dass
Datenmanagement zu einer Kernkompetenz fur erfolgreiche Unternehmen
dieser Zeit geworden ist. Damit Daten ihren ganzen Wert entfalten
koennen, mussen sie stets in angemessener Qualitat zur Verfugung
stehen. Dies gilt besonders fur Stammdaten, die zentralen
Geschaftsobjekte eines Unternehmens. Dieses Buch zeigt einen
ganzheitlichen Ansatz zum qualitatsbewussten Management von
Stammdaten auf und richtet sich damit sowohl an Praktiker als auch
an die Wissenschaft. Das "Framework fur
Stammdatenqualitatsmanagement" wurde im Rahmen des "Competence
Center Corporate Data Quality" der Universitat St. Gallen seit dem
Jahr 2006 gemeinsam mit Unternehmen aus unterschiedlichen
Industrien in zahlreichen praktischen Anwendungen entwickelt und
verbessert. Neben den theoretischen Grundlagen raumt das Buch der
praktischen Sicht mit 10 Fallstudien grossen Raum ein, die
erfolgreich durchgefuhrte Datenqualitatsprojekte praxisnah
aufbereiten. Schliesslich fuhrt das Buch noch Methoden und
Werkzeuge fur das Datenqualitatsmanagement auf, die
(Stamm-)datenmanager bei Projekten im eigenen betrieblichen Umfeld
unterstutzen koennen.
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