Knowledge Transfer-based Recommendations to Enable Self-Service Business Intelligence
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Enterprises nowadays face multiple challenges while operating their businesses. These result from the continuous change in the business environment, which has become more complex and dynamic. Moreover, this environment is influenced by globalization, legal changes, volatile markets, and technical progress. In this complex business world, the integration of Business Intelligence (BI) systems in enterprises will help decision-makers and management by providing them with important information at the right time, enabling them to react quickly to dynamic changes in the market.
BI has been widely deployed in enterprises in order to help the employees in their decision-making process at all levels. Statistics from Gartner Group show that investment in the BI domain has recently been very high. On the other hand, different studies and market researches show that the pervasiveness and the percentage usage rate of BI are still very low. The reason behind this is the complexity of the use of BI systems. Enterprise users often lack the analytical and technical skills required to use these systems. Business users cannot get the needed information unless they ask for support from IT or power users. The resulting large number of business user requests leads to overload at the power users, who have become a bigger bottleneck than before.
To address the above-mentioned issues and to improve the usage rate of BI systems, a new concept for self-service BI is proposed. Within this system, the knowledge of power users is extracted in form of analysis paths and stored in a knowledge repository. This knowledge then is delivered to business users in form of recommendations in real time while they use the BI system to enable them to get answers about their business questions at the right time.
BI has been widely deployed in enterprises in order to help the employees in their decision-making process at all levels. Statistics from Gartner Group show that investment in the BI domain has recently been very high. On the other hand, different studies and market researches show that the pervasiveness and the percentage usage rate of BI are still very low. The reason behind this is the complexity of the use of BI systems. Enterprise users often lack the analytical and technical skills required to use these systems. Business users cannot get the needed information unless they ask for support from IT or power users. The resulting large number of business user requests leads to overload at the power users, who have become a bigger bottleneck than before.
To address the above-mentioned issues and to improve the usage rate of BI systems, a new concept for self-service BI is proposed. Within this system, the knowledge of power users is extracted in form of analysis paths and stored in a knowledge repository. This knowledge then is delivered to business users in form of recommendations in real time while they use the BI system to enable them to get answers about their business questions at the right time.
| Erscheinungsdatum | 14.10.2019 |
|---|---|
| Reihe/Serie | Oldenburger Schriften zur Wirtschaftsinformatik ; 27 |
| Verlagsort | Düren |
| Sprache | englisch |
| Maße | 148 x 210 mm |
| Gewicht | 269 g |
| Themenwelt | Mathematik / Informatik ► Informatik |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Schlagworte | Business Intelligence • Knowledge Transfer Model • Recommender Systems • Self-Service BI |
| ISBN-10 | 3-8440-6956-9 / 3844069569 |
| ISBN-13 | 978-3-8440-6956-3 / 9783844069563 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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