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Biblioqrafik təsvir | Nabibeyova , G.C. Expanding the intellectual capabilities of OLAP technology using neural networks / G.C. Nabibeyova // Problems of Information Society. - 2024. - N: vol.15, no.2. - P. 43-48. | Annotasiya | The article highlights the main characteristics, features and structure of Online Analytical
Processing systems based on the same technology that perform online analytical processing of
data. This technology allows analysts to explore and navigate a multidimensional indicator
structure called an online analytical processing cube (data cube). Indicators (measures) of data
cube play an important role in the decision-making process. To solve certain problems, these
measures often need to be classified or grouped. Moreover, empty measures are common in data
cube. This fact negatively affects strategic decision making. Unfortunately, online analytical
processing itself is not well suited for classifying, clustering, and predicting empty measures of
data cube in the presence of large data. In this regard, today there is a need to use new
technologies to solve such problems. Such technologies include neural networks. The article
discusses the problem of integrating online analytical processing and a neural network, showing
the possibilities and advantages of such integration. It mentions that in the case of big data, the
integration of OLAP and neural networks is very effective in solving problems of classification,
clustering and empty measure prediction of data cube. An architectural and technological model
for the integration of online analytical processing and neural networks is presented.
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