| Autor: |
Alexopoulos, Andreas, Becerra, Yolanda, Boehm, Omer, Bravos, George, Chatzigiannakis, Vasilis, Cugnasco, Cesare, Giorgos Demetriou, Iliada Eleftheriou, Fodor, Lidija, Fotis, Spiros, Sotiris Ioannidis, Dusan Jakovetic, Kallipolitis, Leonidas, Katusic, Vlatka, Kavakli, Evangelia, Kopanaki, Despina, Leventis, Christoforos, Marcos, Mario Maawad, Pozuelo, Ramon Martin De, Martínez, Miquel, Milosevic, Nemanja, Pages, Enric, Ristow, Gerald, Hernan Ruiz-Ocampo, Rizos Sakellariou, Raül Sirvent, Srdjan Skrbic, Spais, Ilias, Giorgos Vasiliadis, Vinov, Michael |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| DOI: |
10.5281/zenodo.4540174 |
| Popis: |
A large number of EU organizations already leverage Big Data pools todrive value and investments. This trend also applies to the banking sector. As aspecific example, CaixaBank currently manages more than 300 different datasources (more than 4 PetaBytes of data and increasing) and more than 700 internaland external active users and services are processing them every day. In order toharness value from such high-volume and high-variety of data, banks need to resolveseveral challenges, such as finding efficient ways to perform Big Data analyticsand to provide solutions that help to increase the involvement of bank employees,the true decision makers. In this book chapter, we describe how thesechallenges are resolved by the self-service solution developed within the I-BiDaaSproject. In more detail, we present three CaixaBank use cases, namely i) Analysisof relationships through IP addresses; ii) Advanced Analysis of bank transfer paymentin financial terminal; and iii) Enhanced control of customers to online banking,and describe how the corresponding requirements are mapped to specific technicaland business KPIs. For each use case, we present the architecture, data analysisand visualization provided by the I-BiDaaS solution, reporting on the achieved results,domain-specific impact, and lessons learned. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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